1067 writes to ShortName
Microsoft.ML.Data (319)
Commands\CrossValidationCommand.cs (22)
30[Argument(ArgumentType.Multiple, HelpText = "Trainer to use", ShortName = "tr", SignatureType = typeof(SignatureTrainer))] 36[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))] 39[Argument(ArgumentType.AtMostOnce, HelpText = "Results summary filename", ShortName = "sf")] 42[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2)] 45[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 48[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 51[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 54[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 6)] 57[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for stratification", ShortName = "strat", SortOrder = 7)] 61Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 64[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of folds in k-fold cross-validation", ShortName = "k")] 67[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Use threads", ShortName = "threads")] 70[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Normalize option for the feature column", ShortName = "norm")] 73[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should cache input training data", ShortName = "cache")] 77Name = "PreTransform", ShortName = "prexf", SignatureType = typeof(SignatureDataTransform))] 80[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The validation data file", ShortName = "valid")] 83[Argument(ArgumentType.Multiple, HelpText = "Output calibrator", ShortName = "cali", NullName = "<None>", SignatureType = typeof(SignatureCalibrator))] 86[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of instances to train the calibrator", ShortName = "numcali")] 90ShortName = "dout")] 93[Argument(ArgumentType.AtMostOnce, HelpText = "Print the run/fold index in per-instance output", ShortName = "opf")] 96[Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should collate metrics or store them in per-folds files", ShortName = "collate")] 99[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should load predictor from input model and use it as the initial model state", ShortName = "cont")]
Commands\DataCommand.cs (9)
26[Argument(ArgumentType.Multiple, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "The data loader", ShortName = "loader", SortOrder = 1, NullName = "<Auto>", SignatureType = typeof(SignatureDataLoader))] 29[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The data file", ShortName = "data", SortOrder = 0)] 32[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Model file to save", ShortName = "out")] 35[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, IsInputFileName = true, HelpText = "Model file to load", ShortName = "in", SortOrder = 90)] 38[Argument(ArgumentType.Multiple, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Load transforms from model file?", ShortName = "loadTrans", SortOrder = 91)] 41[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Random seed", ShortName = "seed", SortOrder = 101)] 44[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Verbose?", ShortName = "v", Hide = true)] 54HelpText = "Desired degree of parallelism in the data pipeline", ShortName = "n")] 58HelpText = "Transform", Name = "Transform", ShortName = "xf", SignatureType = typeof(SignatureDataTransform))]
Commands\EvaluateCommand.cs (13)
126[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 129[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 132[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 136Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 139[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", SignatureType = typeof(SignatureMamlEvaluator))] 176[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 179[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 182[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 185[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 6)] 189Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 192[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", SignatureType = typeof(SignatureMamlEvaluator))] 195[Argument(ArgumentType.AtMostOnce, HelpText = "Results summary filename", ShortName = "sf")] 199ShortName = "dout")]
Commands\SaveDataCommand.cs (4)
33[Argument(ArgumentType.AtMostOnce, HelpText = "File to save the data", ShortName = "dout")] 36[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to include hidden columns", ShortName = "keep")] 95[Argument(ArgumentType.Multiple, HelpText = "Comma separated list of columns to display", ShortName = "cols")] 101[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to include hidden columns", ShortName = "keep")]
Commands\SavePredictorCommand.cs (6)
28[Argument(ArgumentType.AtMostOnce, HelpText = "Model file containing the predictor", ShortName = "in")] 32[Argument(ArgumentType.AtMostOnce, HelpText = "File to save model summary", ShortName = "sum")] 36[Argument(ArgumentType.AtMostOnce, HelpText = "File to save in text format", ShortName = "text")] 40[Argument(ArgumentType.AtMostOnce, HelpText = "File to save in INI format", ShortName = "ini")] 44[Argument(ArgumentType.AtMostOnce, HelpText = "File to save in C++ code", ShortName = "code")] 48[Argument(ArgumentType.AtMostOnce, HelpText = "File to save in binary format", ShortName = "bin")]
Commands\ScoreCommand.cs (8)
46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for features when scorer is not defined", ShortName = "feat")] 49[Argument(ArgumentType.AtMostOnce, HelpText = "Group column name", ShortName = "group")] 54Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 63[Argument(ArgumentType.LastOccurrenceWins, HelpText = "File to save the data", ShortName = "dout")] 66[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to include hidden columns", ShortName = "keep")] 69[Argument(ArgumentType.Multiple, HelpText = "Post processing transform", ShortName = "pxf", SignatureType = typeof(SignatureDataTransform))] 72[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to output all columns or just scores", ShortName = "all")] 76Name = "OutputColumn", ShortName = "outCol")]
Commands\ShowSchemaCommand.cs (4)
29[Argument(ArgumentType.AtMostOnce, HelpText = "Show all steps in transform chain", ShortName = "steps")] 32[Argument(ArgumentType.AtMostOnce, HelpText = "Show the metadata types", ShortName = "metaTypes")] 36[Argument(ArgumentType.AtMostOnce, HelpText = "Show the metadata types and values", ShortName = "meta,metaVals,metaValues")] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Show slot names", ShortName = "slots", Hide = true)]
Commands\TestCommand.cs (9)
27[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2)] 30[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 33[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 36[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 39[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 6)] 44Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 50[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))] 53[Argument(ArgumentType.AtMostOnce, HelpText = "Results summary filename", ShortName = "sf")] 57ShortName = "dout")]
Commands\TrainCommand.cs (14)
43[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2)] 46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 49[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 52[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 55[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 6)] 59Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 62[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Normalize option for the feature column", ShortName = "norm")] 65[Argument(ArgumentType.Multiple, HelpText = "Trainer to use", ShortName = "tr", SignatureType = typeof(SignatureTrainer))] 68[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The validation data file", ShortName = "valid")] 71[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The test data file", ShortName = "test")] 74[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should cache input training data", ShortName = "cache")] 77[Argument(ArgumentType.Multiple, HelpText = "Output calibrator", ShortName = "cali", NullName = "<None>", SignatureType = typeof(SignatureCalibrator))] 80[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of instances to train the calibrator", ShortName = "numcali")] 83[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should load predictor from input model and use it as the initial model state", ShortName = "cont")]
Commands\TrainTestCommand.cs (17)
25[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The test data file", ShortName = "test", SortOrder = 1)] 28[Argument(ArgumentType.Multiple, HelpText = "Trainer to use", ShortName = "tr", SignatureType = typeof(SignatureTrainer))] 34[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))] 37[Argument(ArgumentType.AtMostOnce, HelpText = "Results summary filename", ShortName = "sf")] 40[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2)] 43[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3)] 46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4)] 49[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 5)] 52[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 6)] 56Name = "CustomColumn", ShortName = "col", SortOrder = 10)] 59[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Normalize option for the feature column", ShortName = "norm")] 62[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The validation data file", ShortName = "valid")] 65[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should cache input training data", ShortName = "cache")] 68[Argument(ArgumentType.Multiple, HelpText = "Output calibrator", ShortName = "cali", NullName = "<None>", SignatureType = typeof(SignatureCalibrator))] 71[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of instances to train the calibrator", ShortName = "numcali")] 75ShortName = "dout")] 78[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should load predictor from input model and use it as the initial model state", ShortName = "cont")]
DataLoadSave\Binary\BinaryLoader.cs (3)
43[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The number of worker decompressor threads to use", ShortName = "t")] 49"Larger values will make the shuffling more random, but use more memory. Set to 0 to use only block shuffling.", ShortName = "pb")] 2108[Argument(ArgumentType.AtMostOnce, HelpText = "Verbose?", ShortName = "v", Hide = true)]
DataLoadSave\Binary\BinarySaver.cs (4)
36[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The compression scheme to use for the blocks", ShortName = "comp")] 39[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The block-size heuristic will choose no more than this many rows to have per block, can be set to null to indicate that there is no inherent limit", ShortName = "rpb")] 42[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The block-size heuristic will attempt to have about this many bytes across all columns per block, can be set to null to accept the indicated max-rows-per-block as the number of rows per block", ShortName = "bpb")] 45[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, this forces a deterministic block order during writing", ShortName = "det")]
DataLoadSave\Database\DatabaseLoader.cs (4)
242[Argument(ArgumentType.Multiple, HelpText = "Source index range(s) of the column", ShortName = "src")] 248[Argument(ArgumentType.Multiple, HelpText = "For a key column, this defines the range of values", ShortName = "key")] 330[Argument(ArgumentType.AtMostOnce, HelpText = "Force scalar columns to be treated as vectors of length one", ShortName = "vector")] 352Name = "Column", ShortName = "col", SortOrder = 1)]
DataLoadSave\LegacyCompositeDataLoader.cs (2)
35[Argument(ArgumentType.Multiple, HelpText = "The data loader", ShortName = "loader", SignatureType = typeof(SignatureDataLoader))] 38[Argument(ArgumentType.Multiple, HelpText = "Transform", Name = "Transform", ShortName = "xf", SignatureType = typeof(SignatureDataTransform))]
DataLoadSave\Text\TextLoader.cs (21)
130[Argument(ArgumentType.Multiple, HelpText = "Source index range(s) of the column", ShortName = "src")] 136[Argument(ArgumentType.Multiple, HelpText = "For a key column, this defines the range of values", ShortName = "key")] 323ShortName = "auto")] 333ShortName = "var")] 339[Argument(ArgumentType.AtMostOnce, HelpText = "This range includes only other indices not specified", ShortName = "other")] 345[Argument(ArgumentType.AtMostOnce, HelpText = "Force scalar columns to be treated as vectors of length one", ShortName = "vector")] 439ShortName = "quote")] 455[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the input may include sparse representations", ShortName = "sparse")] 463ShortName = "size")] 466[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Source column separator. Options: tab, space, comma, single character", ShortName = "sep")] 473[Argument(ArgumentType.AtMostOnce, Name = nameof(Separator), Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Source column separator.", ShortName = "sep")] 479[Argument(ArgumentType.AtMostOnce, Name = "Decimal Marker", HelpText = "Character symbol used to separate the integer part from the fractional part of a number written in decimal form.", ShortName = "decimal")] 486Name = "Column", ShortName = "col", SortOrder = 1)] 492[Argument(ArgumentType.AtMostOnce, HelpText = "Remove trailing whitespace from lines", ShortName = "trim")] 499[Argument(ArgumentType.AtMostOnce, ShortName = "header", 506[Argument(ArgumentType.AtMostOnce, HelpText = "Use separate parsing threads?", ShortName = "threads", Hide = true)] 513[Argument(ArgumentType.AtMostOnce, HelpText = "Escape new line characters inside a quoted field? If AllowQuoting is false, this argument is ignored.", ShortName = "multilines", Hide = true)] 520ShortName = "hf", IsInputFileName = true)] 526[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of rows to produce", ShortName = "rows", Hide = true)] 532[Argument(ArgumentType.AtMostOnce, HelpText = "Character to use to escape quotes inside quoted fields. It can't be a character used as separator.", ShortName = "escapechar")] 541[Argument(ArgumentType.AtMostOnce, HelpText = "If true, empty float fields will be loaded as NaN. If false, they'll be loaded as 0. Default is false.", ShortName = "missingrealnan")]
DataLoadSave\Text\TextSaver.cs (4)
36[Argument(ArgumentType.AtMostOnce, HelpText = "Separator", ShortName = "sep")] 39[Argument(ArgumentType.AtMostOnce, HelpText = "Force dense format", ShortName = "dense")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Output the comment containing the loader settings", ShortName = "schema")] 50[Argument(ArgumentType.AtMostOnce, HelpText = "Output the header", ShortName = "header")]
DataLoadSave\Transpose\TransposeLoader.cs (1)
38[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The number of worker decompresser threads to use", ShortName = "t")]
DataLoadSave\Transpose\TransposeSaver.cs (1)
35[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Write a copy of the data in row-wise format, in addition to the transposed data. This will increase performance for mixed applications while taking significantly more space.", ShortName = "row")]
Dirty\ChooseColumnsByIndexTransform.cs (2)
27[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column indices to select", Name = "Index", ShortName = "ind")] 30[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, selected columns are dropped instead of kept, with the order of kept columns being the same as the original", ShortName = "d")]
EntryPoints\InputBase.cs (2)
31[Argument(ArgumentType.Required, ShortName = "data", HelpText = "The data to be used for evaluation.", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 34[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name.", ShortName = "name", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
EntryPoints\SummarizePredictor.cs (1)
23[Argument(ArgumentType.Required, ShortName = "predictorModel", HelpText = "The predictor to summarize")]
Evaluators\AnomalyDetectionEvaluator.cs (4)
36[Argument(ArgumentType.AtMostOnce, HelpText = "Number of top-scored predictions to display", ShortName = "n")] 42[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUC calculation. If 0, AUC is not computed. If -1, the whole dataset is used", ShortName = "numauc")] 630[Argument(ArgumentType.AtMostOnce, HelpText = "Number of top-scored predictions to display", ShortName = "n")] 636[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUC calculation. If 0, AUC is not computed. If -1, the whole dataset is used", ShortName = "numauc")]
Evaluators\BinaryClassifierEvaluator.cs (10)
38[Argument(ArgumentType.AtMostOnce, HelpText = "Use raw score value instead of probability for classification thresholding", ShortName = "useRawScore")] 41[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for p/r curve generation. Specify 0 for no p/r curve generation", ShortName = "numpr")] 44[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUC calculation. If 0, AUC is not computed. If -1, the whole dataset is used", ShortName = "numauc")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUPRC calculation. Specify 0 for no AUPRC calculation", ShortName = "numauprc")] 1289[Argument(ArgumentType.AtMostOnce, HelpText = "Probability column name", ShortName = "prob")] 1295[Argument(ArgumentType.AtMostOnce, HelpText = "Use raw score value instead of probability for classification thresholding", ShortName = "useRawScore")] 1298[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for p/r curve generation. Specify 0 for no p/r curve generation", ShortName = "numpr")] 1301[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUC calculation. If 0, AUC is not computed. If -1, the whole dataset is used", ShortName = "numauc")] 1304[Argument(ArgumentType.AtMostOnce, HelpText = "The number of samples to use for AUPRC calculation. Specify 0 for no AUPRC calculation", ShortName = "numauprc")] 1307[Argument(ArgumentType.AtMostOnce, HelpText = "Precision-Recall results filename", ShortName = "pr", Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
Evaluators\ClusteringEvaluator.cs (4)
37ShortName = "dbi")] 767[Argument(ArgumentType.AtMostOnce, HelpText = "Features column name", ShortName = "feat")] 770[Argument(ArgumentType.AtMostOnce, HelpText = "Calculate DBI? (time-consuming unsupervised metric)", ShortName = "dbi")] 773[Argument(ArgumentType.AtMostOnce, HelpText = "Output top K clusters", ShortName = "topk")]
Evaluators\MamlEvaluator.cs (4)
60[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels.", ShortName = "lab")] 63[Argument(ArgumentType.AtMostOnce, HelpText = "Weight column name.", ShortName = "weight")] 68[Argument(ArgumentType.AtMostOnce, HelpText = "Score column name.", ShortName = "score")] 73[Argument(ArgumentType.Multiple, HelpText = "Stratification column name.", Name = "StratColumn", ShortName = "strat")]
Evaluators\MulticlassClassificationEvaluator.cs (6)
34[Argument(ArgumentType.AtMostOnce, HelpText = "Output top K accuracy", ShortName = "topkacc")] 37[Argument(ArgumentType.AtMostOnce, HelpText = "Use the textual class label names in the report, if available", ShortName = "n")] 874[Argument(ArgumentType.AtMostOnce, HelpText = "Output top-K accuracy.", ShortName = "topkacc")] 877[Argument(ArgumentType.AtMostOnce, HelpText = "Output top-K classes.", ShortName = "topk")] 880[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of classes in confusion matrix.", ShortName = "nccf")] 883[Argument(ArgumentType.AtMostOnce, HelpText = "Output per class statistics and confusion matrix.", ShortName = "opcs")]
Evaluators\MultiOutputRegressionEvaluator.cs (2)
617[Argument(ArgumentType.Multiple, HelpText = "Loss function", ShortName = "loss")] 620[Argument(ArgumentType.AtMostOnce, HelpText = "Suppress labels and scores in per-instance outputs?", ShortName = "noScores")]
Evaluators\QuantileRegressionEvaluator.cs (2)
465[Argument(ArgumentType.Multiple, HelpText = "Loss function", ShortName = "loss")] 468[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Quantile index to select", ShortName = "ind")]
Evaluators\RankingEvaluator.cs (7)
37[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum truncation level for computing (N)DCG", ShortName = "t")] 43[Argument(ArgumentType.AtMostOnce, HelpText = "Label relevance gains", ShortName = "gains")] 46[Argument(ArgumentType.AtMostOnce, HelpText = "Generate per-group (N)DCG", ShortName = "ogs")] 857[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for the group ID", ShortName = "group")] 860[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum truncation level for computing (N)DCG", ShortName = "t")] 863[Argument(ArgumentType.AtMostOnce, HelpText = "Label relevance gains", ShortName = "gains")] 866[Argument(ArgumentType.AtMostOnce, HelpText = "Group summary filename", ShortName = "gsf", Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
Evaluators\RegressionEvaluator.cs (1)
343[Argument(ArgumentType.Multiple, HelpText = "Loss function", ShortName = "loss")]
Evaluators\RegressionEvaluatorBase.cs (1)
20[Argument(ArgumentType.Multiple, HelpText = "Loss function", ShortName = "loss")]
Model\Pfa\SavePfaCommand.cs (6)
37[Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should allow set operations.", ShortName = "set", SortOrder = 3, Hide = true)] 40[Argument(ArgumentType.AtMostOnce, HelpText = "Comma delimited list of input column names to drop", ShortName = "idrop", SortOrder = 4)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "Comma delimited list of output column names to drop", ShortName = "odrop", SortOrder = 5)] 46[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the inputs should also map to the outputs.", ShortName = "input", SortOrder = 6)] 49[Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.", ShortName = "pred", SortOrder = 7)] 52[Argument(ArgumentType.AtMostOnce, HelpText = "Format option for the JSON exporter.", ShortName = "format", SortOrder = 8)]
Prediction\Calibrator.cs (6)
1637[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The slope parameter of f(x) = 1 / (1 + exp(slope * x + offset)", ShortName = "a")] 1640[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The offset parameter of f(x) = 1 / (1 + exp(slope * x + offset)", ShortName = "b")] 2130[Argument(ArgumentType.Required, ShortName = "uncalibratedPredictorModel", HelpText = "The predictor to calibrate", SortOrder = 2)] 2133[Argument(ArgumentType.Required, ShortName = "maxRows", HelpText = "The maximum number of examples to train the calibrator on", SortOrder = 3)] 2144[Argument(ArgumentType.AtMostOnce, ShortName = "slope", HelpText = "The slope parameter of the calibration function 1 / (1 + exp(slope * x + offset)", SortOrder = 1)] 2147[Argument(ArgumentType.AtMostOnce, ShortName = "offset", HelpText = "The offset parameter of the calibration function 1 / (1 + exp(slope * x + offset)", SortOrder = 3)]
Prediction\PredictionEngine.cs (4)
184[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to throw an error if a column exists in the output schema but not the output object.", ShortName = "ignore", SortOrder = 50)] 187[Argument(ArgumentType.AtMostOnce, HelpText = "Additional settings of the input schema.", ShortName = "input", SortOrder = 50)] 190[Argument(ArgumentType.AtMostOnce, HelpText = "Additional settings of the output schema.", ShortName = "output")] 193[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the prediction engine owns the transformer and should dispose of it.", ShortName = "own")]
Scorers\FeatureContributionCalculation.cs (2)
46[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not output of Features contribution should be normalized", ShortName = "norm", SortOrder = 3)] 49[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not output of Features contribution in string key-value format", ShortName = "str", SortOrder = 4)]
Scorers\MulticlassClassificationScorer.cs (2)
38[Argument(ArgumentType.AtMostOnce, HelpText = "Score Column Name.", ShortName = "scn")] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Predicted Label Column Name.", ShortName = "plcn")]
Scorers\PredictedLabelScorerBase.cs (2)
24[Argument(ArgumentType.AtMostOnce, HelpText = "Value for classification thresholding", ShortName = "t")] 27[Argument(ArgumentType.AtMostOnce, HelpText = "Specify which predictor output to use for classification thresholding", ShortName = "tcol")]
Scorers\RowToRowScorerBase.cs (1)
315[Argument(ArgumentType.AtMostOnce, HelpText = "Output column: The suffix to append to the default column names", ShortName = "ex")]
Training\TrainerInputBase.cs (8)
26[Argument(ArgumentType.Required, ShortName = "data", HelpText = "The data to be used for training", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 32[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 39[Argument(ArgumentType.AtMostOnce, HelpText = "Normalize option for the feature column", ShortName = "norm", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 48[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether trainer should cache input training data", ShortName = "cache", SortOrder = 6, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 63[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 79[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 94[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 109[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example groupId", ShortName = "groupId", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
Transforms\BootstrapSamplingTransformer.cs (3)
41ShortName = "comp")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Whether we should attempt to shuffle the source data. By default on, but can be turned off for efficiency.", ShortName = "si")] 50[Argument(ArgumentType.LastOccurrenceWins, HelpText = "When shuffling the output, the number of output rows to keep in that pool. Note that shuffling of output is completely distinct from shuffling of input.", ShortName = "pool")]
Transforms\ColumnBindingsBase.cs (4)
19[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the new column", ShortName = "name")] 22[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the source column", ShortName = "src")] 116[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the new column", ShortName = "name")] 119[Argument(ArgumentType.Multiple, HelpText = "Name of the source column", ShortName = "src")]
Transforms\ColumnConcatenatingTransformer.cs (4)
68[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the new column", ShortName = "name")] 76[Argument(ArgumentType.Multiple, HelpText = "Names of the source columns", ShortName = "src")] 121Name = "Column", ShortName = "col", SortOrder = 1)] 129Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\ColumnCopying.cs (1)
142Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\ColumnSelecting.cs (4)
211[Argument(ArgumentType.Multiple, HelpText = "List of columns to keep.", ShortName = "keepcol", SortOrder = 1)] 214[Argument(ArgumentType.Multiple, HelpText = "List of columns to drop.", ShortName = "dropcol", SortOrder = 2)] 217[Argument(ArgumentType.AtMostOnce, HelpText = "Specifies whether to keep or remove hidden columns.", ShortName = "hidden", SortOrder = 3)] 220[Argument(ArgumentType.AtMostOnce, HelpText = "Specifies whether to ignore columns that are missing from the input.", ShortName = "ignore", SortOrder = 4)]
Transforms\FeatureContributionCalculationTransformer.cs (1)
47[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not output of Features contribution should be normalized", ShortName = "norm", SortOrder = 5)]
Transforms\GenerateNumberTransform.cs (4)
37[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the new column", ShortName = "name")] 40[Argument(ArgumentType.AtMostOnce, HelpText = "Use an auto-incremented integer starting at zero instead of a random number", ShortName = "cnt")] 90Name = "Column", ShortName = "col", SortOrder = 1)] 93[Argument(ArgumentType.AtMostOnce, HelpText = "Use an auto-incremented integer starting at zero instead of a random number", ShortName = "cnt")]
Transforms\Hashing.cs (7)
40Name = "Column", ShortName = "col", SortOrder = 1)] 44ShortName = "bits", SortOrder = 2)] 51ShortName = "ord")] 55ShortName = "ih")] 64[Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 31, inclusive", ShortName = "bits")] 71ShortName = "ord")] 75ShortName = "ih")]
Transforms\KeyToValue.cs (1)
60Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\KeyToVector.cs (1)
88Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\LabelConvertTransform.cs (1)
49Name = "Column", ShortName = "col")]
Transforms\LabelIndicatorTransform.cs (3)
49[Argument(ArgumentType.AtMostOnce, HelpText = "The positive example class for binary classification.", ShortName = "index")] 71[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 74[Argument(ArgumentType.AtMostOnce, HelpText = "Label of the positive class.", ShortName = "index")]
Transforms\NAFilter.cs (1)
38[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\NormalizeColumn.cs (15)
56Name = "MaxTrainingExamples", ShortName = "maxtrain")] 76[Argument(ArgumentType.AtMostOnce, Name = "FixZero", HelpText = "Whether to map zero to zero, preserving sparsity", ShortName = "zero")] 109[Argument(ArgumentType.AtMostOnce, HelpText = "Max number of bins, power of 2 recommended", ShortName = "bins")] 167[Argument(ArgumentType.AtMostOnce, Name = "FixZero", HelpText = "Whether to map zero to zero, preserving sparsity", ShortName = "zero")] 173[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 185[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use CDF as the output", ShortName = "cdf")] 192Name = "MaxTrainingExamples", ShortName = "maxtrain")] 218[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use CDF as the output", ShortName = "cdf")] 221[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 229[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 232[Argument(ArgumentType.AtMostOnce, HelpText = "Max number of bins, power of 2 recommended", ShortName = "bins")] 246[Argument(ArgumentType.Required, HelpText = "Label column for supervised binning", ShortName = "label,lab", 256[Argument(ArgumentType.AtMostOnce, HelpText = "Should the data be centered around 0", Name = "CenterData", ShortName = "center", SortOrder = 1)] 259[Argument(ArgumentType.AtMostOnce, HelpText = "Minimum quantile value. Defaults to 25", Name = "QuantileMin", ShortName = "qmin", SortOrder = 2)] 262[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum quantile value. Defaults to 75", Name = "QuantileMax", ShortName = "qmax", SortOrder = 3)]
Transforms\RangeFilter.cs (1)
35[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", ShortName = "col", SortOrder = 1, Purpose = SpecialPurpose.ColumnName)]
Transforms\RowShufflingTransformer.cs (5)
46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The pool will have this many rows", ShortName = "rows")] 50[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, the transform will not attempt to shuffle the input cursor but only shuffle based on the pool. This parameter has no effect if the input data was not itself shufflable.", ShortName = "po")] 53[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, the transform will always provide a shuffled view.", ShortName = "force")] 56[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, the transform will always shuffle the input. The default value is the same as forceShuffle.", ShortName = "forceSource")] 59[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The random seed to use for forced shuffling.", ShortName = "seed")]
Transforms\SkipTakeFilter.cs (4)
55[Argument(ArgumentType.AtMostOnce, HelpText = SkipHelp, ShortName = "s", SortOrder = 1)] 58[Argument(ArgumentType.AtMostOnce, HelpText = TakeHelp, ShortName = "t", SortOrder = 2)] 64[Argument(ArgumentType.Required, HelpText = Options.TakeHelp, ShortName = "c,n,t", SortOrder = 1)] 70[Argument(ArgumentType.Required, HelpText = Options.SkipHelp, ShortName = "c,n,s", SortOrder = 1)]
Transforms\SlotsDroppingTransformer.cs (1)
44Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\TrainAndScoreTransformer.cs (13)
28ShortName = "feat", SortOrder = 1, 32[Argument(ArgumentType.AtMostOnce, HelpText = "Group column name", ShortName = "group", SortOrder = 100, 38Name = "CustomColumn", ShortName = "col", SortOrder = 101, Purpose = SpecialPurpose.ColumnSelector)] 45ShortName = "in", SortOrder = 2)] 112ShortName = "feat", SortOrder = 102, Purpose = SpecialPurpose.ColumnName)] 115[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 103, 119[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", 123[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", 127[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 106, 133Name = "CustomColumn", ShortName = "col", SortOrder = 110, Purpose = SpecialPurpose.ColumnSelector)] 149[Argument(ArgumentType.Multiple, HelpText = "Trainer to use", ShortName = "tr", NullName = "<None>", SortOrder = 1, SignatureType = typeof(SignatureTrainer))] 152[Argument(ArgumentType.Multiple, HelpText = "Output calibrator", ShortName = "cali", NullName = "<None>", SignatureType = typeof(SignatureCalibrator))] 155[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of instances to train the calibrator", ShortName = "numcali")]
Transforms\TypeConverting.cs (7)
61[Argument(ArgumentType.AtMostOnce, HelpText = "The result type", ShortName = "type")] 64[Argument(ArgumentType.Multiple, HelpText = "For a key column, this defines the cardinality/count of valid key values", ShortName = "key", Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 67[Argument(ArgumentType.AtMostOnce, HelpText = "For a key column, this defines the range of values", ShortName = "key", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 132[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:type:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 135[Argument(ArgumentType.AtMostOnce, HelpText = "The result type", ShortName = "type", SortOrder = 2)] 138[Argument(ArgumentType.Multiple, HelpText = "For a key column, this defines the range of values", ShortName = "key", Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 141[Argument(ArgumentType.AtMostOnce, HelpText = "For a key column, this defines the range of values", ShortName = "key", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
Transforms\ValueMapping.cs (5)
410[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 413[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The data file containing the terms", ShortName = "data", SortOrder = 2)] 416[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the column containing the keys", ShortName = "keyCol, term, TermColumn")] 419[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the column containing the values", ShortName = "valueCol, value")] 427ShortName = "key")]
Transforms\ValueToKeyMappingTransformer.cs (7)
45[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of terms to keep when auto-training", ShortName = "max")] 58[Argument(ArgumentType.AtMostOnce, HelpText = "Whether key value metadata should be text, regardless of the actual input type", ShortName = "textkv", Hide = true)] 99[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of keys to keep per column when auto-training", ShortName = "max", SortOrder = 5)] 108[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "Data file containing the terms", ShortName = "data", SortOrder = 110, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 115[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the text column containing the terms", ShortName = "termCol", SortOrder = 112, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 129[Argument(ArgumentType.AtMostOnce, HelpText = "Whether key value metadata should be text, regardless of the actual input type", ShortName = "textkv", SortOrder = 114, Hide = true)] 136[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
Utils\LossFunctions.cs (3)
212[Argument(ArgumentType.AtMostOnce, HelpText = "Margin value", ShortName = "marg")] 311[Argument(ArgumentType.AtMostOnce, HelpText = "Smoothing constant", ShortName = "smooth")] 427[Argument(ArgumentType.AtMostOnce, HelpText = "Beta (dilation)", ShortName = "beta")]
Microsoft.ML.Ensemble (39)
EntryPoints\CreateEnsemble.cs (8)
47[Argument(ArgumentType.Required, ShortName = "models", HelpText = "The models to combine into an ensemble", SortOrder = 1)] 53[Argument(ArgumentType.Required, ShortName = "models", HelpText = "The models to combine into an ensemble", SortOrder = 1)] 56[Argument(ArgumentType.AtMostOnce, ShortName = "validate", HelpText = "Whether to validate that all the pipelines are identical", SortOrder = 5)] 62[Argument(ArgumentType.AtMostOnce, ShortName = "combiner", HelpText = "The combiner used to combine the scores", SortOrder = 2)] 68[Argument(ArgumentType.AtMostOnce, ShortName = "combiner", HelpText = "The combiner used to combine the scores", SortOrder = 2)] 74[Argument(ArgumentType.AtMostOnce, ShortName = "combiner", HelpText = "The combiner used to combine the scores", SortOrder = 2)] 80[Argument(ArgumentType.AtMostOnce, ShortName = "combiner", HelpText = "The combiner used to combine the scores", SortOrder = 2)] 86[Argument(ArgumentType.AtMostOnce, ShortName = "combiner", HelpText = "The combiner used to combine the scores", SortOrder = 2)]
OutputCombiners\BaseMultiCombiner.cs (1)
21ShortName = "norm", SortOrder = 50)]
OutputCombiners\BaseStacking.cs (1)
20[Argument(ArgumentType.AtMostOnce, ShortName = "vp", SortOrder = 50,
OutputCombiners\MultiStacking.cs (1)
45[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
OutputCombiners\MultiWeightedAverage.cs (1)
47[Argument(ArgumentType.AtMostOnce, HelpText = "The metric type to be used to find the weights for each model", ShortName = "wn", SortOrder = 50)]
OutputCombiners\RegressionStacking.cs (1)
43[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
OutputCombiners\Stacking.cs (1)
42[Argument(ArgumentType.Multiple, HelpText = "Base predictor for meta learning", ShortName = "bp", SortOrder = 50,
OutputCombiners\WeightedAverage.cs (1)
42[Argument(ArgumentType.AtMostOnce, HelpText = "The metric type to be used to find the weights for each model", ShortName = "wn", SortOrder = 50)]
Selector\FeatureSelector\RandomFeatureSelector.cs (1)
27[Argument(ArgumentType.AtMostOnce, HelpText = "The proportion of features to be selected. The range is 0.0-1.0", ShortName = "fp", SortOrder = 50)]
Selector\SubModelSelector\BestDiverseSelectorBinary.cs (1)
28[Argument(ArgumentType.Multiple, HelpText = "The metric type to be used to find the diversity among base learners", ShortName = "dm", SortOrder = 50)]
Selector\SubModelSelector\BestDiverseSelectorMulticlass.cs (1)
29[Argument(ArgumentType.Multiple, HelpText = "The metric type to be used to find the diversity among base learners", ShortName = "dm", SortOrder = 50)]
Selector\SubModelSelector\BestDiverseSelectorRegression.cs (1)
28[Argument(ArgumentType.Multiple, HelpText = "The metric type to be used to find the diversity among base learners", ShortName = "dm", SortOrder = 50)]
Selector\SubModelSelector\BestPerformanceRegressionSelector.cs (1)
24[Argument(ArgumentType.AtMostOnce, HelpText = "The metric type to be used to find the best performance", ShortName = "mn", SortOrder = 50)]
Selector\SubModelSelector\BestPerformanceSelector.cs (1)
24[Argument(ArgumentType.AtMostOnce, HelpText = "The metric type to be used to find the best performance", ShortName = "mn", SortOrder = 50)]
Selector\SubModelSelector\BestPerformanceSelectorMulticlass.cs (1)
24[Argument(ArgumentType.AtMostOnce, HelpText = "The metric type to be used to find the best performance", ShortName = "mn", SortOrder = 50)]
Selector\SubModelSelector\SubModelDataSelector.cs (2)
16[Argument(ArgumentType.AtMostOnce, ShortName = "lp", SortOrder = 50, 21[Argument(ArgumentType.AtMostOnce, ShortName = "vp", SortOrder = 50,
Selector\SubsetSelector\BaseSubsetSelector.cs (1)
19[Argument(ArgumentType.Multiple, HelpText = "The Feature selector", ShortName = "fs", SortOrder = 1)]
Trainer\Binary\EnsembleTrainer.cs (3)
41[Argument(ArgumentType.Multiple, HelpText = "Algorithm to prune the base learners for selective Ensemble", ShortName = "pt", SortOrder = 4)] 46[Argument(ArgumentType.Multiple, HelpText = "Output combiner", ShortName = "oc", SortOrder = 5)] 51[Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureBinaryClassifierTrainer))]
Trainer\EnsembleTrainerBase.cs (5)
29"or the number of base predictors otherwise.", ShortName = "nm", SortOrder = 3)] 33[Argument(ArgumentType.AtMostOnce, HelpText = "Batch size", ShortName = "bs", SortOrder = 107)] 39[Argument(ArgumentType.Multiple, HelpText = "Sampling Type", ShortName = "st", SortOrder = 2)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "All the base learners will run asynchronously if the value is true", ShortName = "tp", SortOrder = 106)] 49ShortName = "sm", SortOrder = 108)]
Trainer\Multiclass\MulticlassDataPartitionEnsembleTrainer.cs (3)
43[Argument(ArgumentType.Multiple, HelpText = "Algorithm to prune the base learners for selective Ensemble", ShortName = "pt", SortOrder = 4)] 47[Argument(ArgumentType.Multiple, HelpText = "Output combiner", ShortName = "oc", SortOrder = 5)] 52[Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureMulticlassClassifierTrainer))]
Trainer\Regression\RegressionEnsembleTrainer.cs (3)
37[Argument(ArgumentType.Multiple, HelpText = "Algorithm to prune the base learners for selective Ensemble", ShortName = "pt", SortOrder = 4)] 41[Argument(ArgumentType.Multiple, HelpText = "Output combiner", ShortName = "oc", SortOrder = 5)] 46[Argument(ArgumentType.Multiple, HelpText = "Base predictor type", ShortName = "bp,basePredictorTypes", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureRegressorTrainer))]
Microsoft.ML.EntryPoints (26)
CrossValidationMacro.cs (10)
68[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for stratification", ShortName = "strat", SortOrder = 6)] 72[Argument(ArgumentType.AtMostOnce, HelpText = "Number of folds in k-fold cross-validation", ShortName = "k", SortOrder = 7)] 80[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 9)] 83[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 10)] 86[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 11)] 89[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 12)] 128[Argument(ArgumentType.AtMostOnce, HelpText = "The label column name", ShortName = "Label", SortOrder = 6)] 131[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 7)] 134[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 8)] 137[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 9)]
CVSplit.cs (1)
30[Argument(ArgumentType.AtMostOnce, ShortName = "strat", HelpText = "Stratification column", SortOrder = 3)]
ImportTextData.cs (4)
22[Argument(ArgumentType.Required, ShortName = "data", HelpText = "Location of the input file", SortOrder = 1)] 25[Argument(ArgumentType.AtMostOnce, ShortName = "schema", HelpText = "Custom schema to use for parsing", SortOrder = 2)] 48[Argument(ArgumentType.Required, ShortName = "data", HelpText = "Location of the input file", SortOrder = 1)] 51[Argument(ArgumentType.Required, ShortName = "args", HelpText = "Arguments", SortOrder = 2)]
PermutationFeatureImportance.cs (4)
44[Argument(ArgumentType.Required, HelpText = "The path to the model file", ShortName = "path", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Use feature weights to pre-filter features", ShortName = "usefw", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 50[Argument(ArgumentType.AtMostOnce, HelpText = "Limit the number of examples to evaluate on", ShortName = "numexamples", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 53[Argument(ArgumentType.AtMostOnce, HelpText = "The number of permutations to perform", ShortName = "permutations", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
TrainTestMacro.cs (6)
35[Argument(ArgumentType.Required, ShortName = "train", HelpText = "The data to be used for training", SortOrder = 1)] 39[Argument(ArgumentType.Required, ShortName = "test", HelpText = "The data to be used for testing", SortOrder = 2)] 64[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 10)] 67[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 11)] 70[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for grouping", ShortName = "group", SortOrder = 12)] 73[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", SortOrder = 13)]
TrainTestSplit.cs (1)
26[Argument(ArgumentType.AtMostOnce, ShortName = "strat", HelpText = "Stratification column", SortOrder = 3)]
Microsoft.ML.FastTree (105)
FastTreeArguments.cs (67)
69[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Option for using derivatives optimized for unbalanced sets", ShortName = "us")] 227[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Comma-separated list of gains associated to each relevance label.", ShortName = "gains")] 234[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Train DCG instead of NDCG", ShortName = "dcg")] 241ShortName = "sort", 250[Argument(ArgumentType.AtMostOnce, HelpText = "max-NDCG truncation to use in the LambdaMART algorithm", ShortName = "n", Hide = true)] 260[Argument(ArgumentType.AtMostOnce, HelpText = "Cost function parameter (w/c)", ShortName = "cf", Hide = true)] 265[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Distance weight 2 adjustment to cost", ShortName = "dw", Hide = true)] 270[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Normalize query lambdas", ShortName = "nql", Hide = true)] 353[Argument(ArgumentType.Multiple, HelpText = "Allows to choose Parallel FastTree Learning Algorithm", ShortName = "parag")] 359[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The number of threads to use", ShortName = "t", NullName = "<Auto>")] 372[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The seed of the random number generator", ShortName = "r1")] 379[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The seed of the active feature selection", ShortName = "r3", Hide = true)] 386[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The entropy (regularization) coefficient between 0 and 1", ShortName = "e")] 393[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The number of histograms in the pool (between 2 and numLeaves)", ShortName = "ps")] 399[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName = "dt")] 405[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to collectivize features during dataset preparation to speed up training", ShortName = "flocks", Hide = true)] 411[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to do split based on multiple categorical feature values.", ShortName = "cat")] 419"there many categorical features.", ShortName = "mcg")] 425[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Maximum categorical split points to consider when splitting on a categorical feature.", ShortName = "maxcat")] 431[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum categorical example percentage in a bin to consider for a split.", ShortName = "mdop")] 437[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum categorical example count in a bin to consider for a split.", ShortName = "mdo")] 443[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Bias for calculating gradient for each feature bin for a categorical feature.", ShortName = "bias")] 452"Bundle.Adjacent(2): Neighbor low population bundle.", ShortName = "bundle")] 460[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Maximum number of distinct values (bins) per feature", ShortName = "mb")] 466[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Sparsity level needed to use sparse feature representation", ShortName = "sp")] 472[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The feature first use penalty coefficient", ShortName = "ffup")] 478[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The feature re-use penalty (regularization) coefficient", ShortName = "frup")] 488[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName = "gainconf")] 494[Argument(ArgumentType.AtMostOnce, HelpText = "The temperature of the randomized softmax distribution for choosing the feature", ShortName = "smtemp")] 500[Argument(ArgumentType.AtMostOnce, HelpText = "Print execution time breakdown to stdout", ShortName = "et")] 506[Argument(ArgumentType.AtMostOnce, HelpText = "Print memory statistics to stdout", ShortName = "memstats")] 513[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The max number of leaves in each regression tree", ShortName = "nl", SortOrder = 2)] 523[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The minimal number of examples allowed in a leaf of a regression tree, out of the subsampled data", ShortName = "mil", SortOrder = 3)] 532[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Total number of decision trees to create in the ensemble", ShortName = "iter", SortOrder = 1)] 541[Argument(ArgumentType.AtMostOnce, HelpText = "The fraction of features (chosen randomly) to use on each iteration", ShortName = "ff")] 547[Argument(ArgumentType.AtMostOnce, HelpText = "Number of trees in each bag (0 for disabling bagging)", ShortName = "bag")] 553[Argument(ArgumentType.AtMostOnce, HelpText = "Percentage of training examples used in each bag", ShortName = "bagfrac")] 563[Argument(ArgumentType.AtMostOnce, HelpText = "The fraction of features (chosen randomly) to use on each split", ShortName = "sf")] 569[Argument(ArgumentType.AtMostOnce, HelpText = "Smoothing paramter for tree regularization", ShortName = "s")] 575[Argument(ArgumentType.AtMostOnce, HelpText = "When a root split is impossible, allow training to proceed", ShortName = "allowempty,dummies", Hide = true)] 583[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The level of feature compression to use", ShortName = "fcomp", Hide = true)] 590[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Compress the tree Ensemble", ShortName = "cmp", Hide = true)] 598[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Print metrics graph for the first test set", ShortName = "graph", Hide = true)] 607[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Print Train and Validation metrics in graph", ShortName = "graphtv", Hide = true)] 614[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Calculate metric values for train/valid/test every k rounds", ShortName = "tf")] 655[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Option for using best regression step trees", ShortName = "bsr")] 661[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Should we use line search for a step size", ShortName = "ls")] 667[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of post-bracket line search steps", ShortName = "lssteps")] 673[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum line search step size", ShortName = "minstep")] 687[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent)", ShortName = "oa")] 694[Argument(ArgumentType.Multiple, HelpText = "Early stopping rule. (Validation set (/valid) is required.)", Name = "EarlyStoppingRule", ShortName = "esr", NullName = "<Disable>")] 721[Argument(ArgumentType.AtMostOnce, HelpText = "Early stopping metrics. (For regression, 1: L1, 2:L2; for ranking, 1:NDCG@1, 3:NDCG@3)", ShortName = "esmt")] 728[Argument(ArgumentType.AtMostOnce, HelpText = "Enable post-training pruning to avoid overfitting. (a validation set is required)", ShortName = "pruning")] 734[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Use window and tolerance for pruning", ShortName = "prtol")] 740[Argument(ArgumentType.AtMostOnce, HelpText = "The tolerance threshold for pruning", ShortName = "prth")] 747[Argument(ArgumentType.AtMostOnce, HelpText = "The moving window size for pruning", ShortName = "prws")] 754[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The learning rate", ShortName = "lr", SortOrder = 4)] 762[Argument(ArgumentType.AtMostOnce, HelpText = "Shrinkage", ShortName = "shrk")] 770[Argument(ArgumentType.AtMostOnce, HelpText = "Dropout rate for tree regularization", ShortName = "tdrop")] 778[Argument(ArgumentType.AtMostOnce, HelpText = "Sample each query 1 in k times in the GetDerivatives function", ShortName = "sr")] 784[Argument(ArgumentType.AtMostOnce, HelpText = "Write the last ensemble instead of the one determined by early stopping", ShortName = "hl")] 790[Argument(ArgumentType.AtMostOnce, HelpText = "Upper bound on absolute value of single tree output", ShortName = "mo")] 796[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Training starts from random ordering (determined by /r1)", ShortName = "rs", Hide = true)] 803[Argument(ArgumentType.AtMostOnce, HelpText = "Filter zero lambdas during training", ShortName = "fzl", Hide = true)] 826[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Freeform defining the scores that should be used as the baseline ranker", ShortName = "basescores", Hide = true)] 834[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Baseline alpha for tradeoffs of risk (0 is normal training)", ShortName = "basealpha", Hide = true)] 843ShortName = "pdff", Hide = true)]
GamClassification.cs (1)
69[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Should we use derivatives optimized for unbalanced sets", ShortName = "us")]
GamModelParameters.cs (1)
557[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to open the GAM visualization page URL", ShortName = "o", SortOrder = 3)]
GamRegression.cs (1)
66[Argument(ArgumentType.AtMostOnce, HelpText = "Metric for pruning. (For regression, 1: L1, 2:L2; default L2)", ShortName = "pmetric")]
GamTrainer.cs (13)
40[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The entropy (regularization) coefficient between 0 and 1", ShortName = "e")] 50[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName = "gainconf")] 56[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Total number of iterations over all features", ShortName = "iter", SortOrder = 1)] 64[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The number of threads to use", ShortName = "t", NullName = "<Auto>")] 70[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The learning rate", ShortName = "lr", SortOrder = 4)] 78[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName = "dt")] 84[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Maximum number of distinct values (bins) per feature", ShortName = "mb")] 90[Argument(ArgumentType.AtMostOnce, HelpText = "Upper bound on absolute value of single output", ShortName = "mo")] 96[Argument(ArgumentType.AtMostOnce, HelpText = "Sample each query 1 in k times in the GetDerivatives function", ShortName = "sr")] 102[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The seed of the random number generator", ShortName = "r1")] 108[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum number of training instances required to form a partition", ShortName = "mi", SortOrder = 3)] 116[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to collectivize features during dataset preparation to speed up training", ShortName = "flocks", Hide = true)] 122[Argument(ArgumentType.AtMostOnce, HelpText = "Enable post-training pruning to avoid overfitting. (a validation set is required)", ShortName = "pruning")]
RandomForestClassification.cs (2)
44[Argument(ArgumentType.AtMostOnce, HelpText = "Number of labels to be sampled from each leaf to make the distribution", ShortName = "qsc")] 158[Argument(ArgumentType.AtMostOnce, HelpText = "Upper bound on absolute value of single tree output", ShortName = "mo")]
SumupPerformanceCommand.cs (9)
37[Argument(ArgumentType.AtMostOnce, HelpText = "The type of IntArray to construct", ShortName = "type", SortOrder = 0)] 40[Argument(ArgumentType.AtMostOnce, HelpText = "The length of each int arrays", ShortName = "len", SortOrder = 1)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "The number of int arrays to create", ShortName = "c", SortOrder = 2)] 46[Argument(ArgumentType.AtMostOnce, HelpText = "The number of bins to have in the int array", ShortName = "b", SortOrder = 3)] 49[Argument(ArgumentType.AtMostOnce, HelpText = "The random parameter, which will differ depending on the type of the feature", ShortName = "p", SortOrder = 4)] 52[Argument(ArgumentType.AtMostOnce, HelpText = "The number of seconds to run sumups in each trial", ShortName = "s", SortOrder = 5)] 55[Argument(ArgumentType.AtMostOnce, HelpText = "Random seed", ShortName = "seed", SortOrder = 101)] 58[Argument(ArgumentType.AtMostOnce, HelpText = "Verbose?", ShortName = "v", Hide = true)] 65HelpText = "Desired degree of parallelism in the data pipeline", ShortName = "n", SortOrder = 6)]
Training\EarlyStoppingCriteria.cs (5)
122[Argument(ArgumentType.AtMostOnce, HelpText = "Tolerance threshold. (Non negative value)", ShortName = "th")] 184[Argument(ArgumentType.AtMostOnce, HelpText = "Threshold in range [0,1].", ShortName = "th")] 188[Argument(ArgumentType.AtMostOnce, HelpText = "The window size.", ShortName = "w")] 290[Argument(ArgumentType.AtMostOnce, HelpText = "Threshold in range [0,1].", ShortName = "th")] 474[Argument(ArgumentType.AtMostOnce, HelpText = "The window size.", ShortName = "w")]
TreeEnsembleFeaturizer.cs (6)
539[Argument(ArgumentType.Multiple, HelpText = "Trainer to use", ShortName = "tr", NullName = "<None>", SortOrder = 1, SignatureType = typeof(SignatureTreeEnsembleTrainer))] 543ShortName = "in", SortOrder = 2)] 547ShortName = "ex", SortOrder = 101)] 551ShortName = "lps", SortOrder = 102)] 564ShortName = "ex", SortOrder = 101)] 568ShortName = "lps", SortOrder = 102)]
Microsoft.ML.ImageAnalytics (36)
ImageGrayscale.cs (1)
56[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
ImageLoader.cs (2)
59[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 62[Argument(ArgumentType.AtMostOnce, HelpText = "Folder where to search for images", ShortName = "folder")]
ImagePixelExtractor.cs (11)
39[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use alpha channel", ShortName = "alpha")] 42[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use red channel", ShortName = "red")] 45[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use green channel", ShortName = "green")] 48[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use blue channel", ShortName = "blue")] 58[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to convert to floating point", ShortName = "conv")] 92[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 95[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use alpha channel", ShortName = "alpha")] 98[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use red channel", ShortName = "red")] 101[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use green channel", ShortName = "green")] 104[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use blue channel", ShortName = "blue")] 113[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to convert to floating point", ShortName = "conv")]
ImageResizer.cs (9)
39[Argument(ArgumentType.AtMostOnce, HelpText = "Width of the resized image", ShortName = "width")] 42[Argument(ArgumentType.AtMostOnce, HelpText = "Height of the resized image", ShortName = "height")] 45[Argument(ArgumentType.AtMostOnce, HelpText = "Resizing method", ShortName = "scale")] 48[Argument(ArgumentType.AtMostOnce, HelpText = "Anchor for cropping", ShortName = "anchor")] 72[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 75[Argument(ArgumentType.Required, HelpText = "Resized width of the image", ShortName = "width")] 78[Argument(ArgumentType.Required, HelpText = "Resized height of the image", ShortName = "height")] 81[Argument(ArgumentType.AtMostOnce, HelpText = "Resizing method", ShortName = "scale")] 84[Argument(ArgumentType.AtMostOnce, HelpText = "Anchor for cropping", ShortName = "anchor")]
VectorToImageTransform.cs (13)
38[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use alpha channel", ShortName = "alpha")] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use red channel", ShortName = "red")] 44[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use green channel", ShortName = "green")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use blue channel", ShortName = "blue")] 57[Argument(ArgumentType.AtMostOnce, HelpText = "Width of the image", ShortName = "width")] 60[Argument(ArgumentType.AtMostOnce, HelpText = "Height of the image", ShortName = "height")] 106[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 109[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use alpha channel", ShortName = "alpha")] 112[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use red channel", ShortName = "red")] 115[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use green channel", ShortName = "green")] 118[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to use blue channel", ShortName = "blue")] 127[Argument(ArgumentType.AtMostOnce, HelpText = "Width of the image", ShortName = "width")] 130[Argument(ArgumentType.AtMostOnce, HelpText = "Height of the image", ShortName = "height")]
Microsoft.ML.KMeansClustering (5)
KMeansPlusPlusTrainer.cs (5)
118[Argument(ArgumentType.AtMostOnce, HelpText = "Cluster initialization algorithm", ShortName = "init")] 125Name = "OptTol", ShortName = "ot")] 132[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of iterations.", ShortName = "maxiter, NumberOfIterations")] 140Name = "AccelMemBudgetMb", ShortName = "accelMemBudgetMb")] 147[Argument(ArgumentType.AtMostOnce, HelpText = "Degree of lock-free parallelism. Defaults to automatic. Determinism not guaranteed.", ShortName = "nt,t,threads", SortOrder = 50)]
Microsoft.ML.LightGbm (28)
LightGbmArguments.cs (3)
136ShortName = "ff")] 148ShortName = "l2")] 162ShortName = "l1")]
LightGbmBinaryTrainer.cs (4)
140[Argument(ArgumentType.AtMostOnce, HelpText = "Use for binary classification when training data is not balanced.", ShortName = "us")] 152ShortName = "ScalePosWeight")] 158[Argument(ArgumentType.AtMostOnce, HelpText = "Parameter for the sigmoid function.", ShortName = "sigmoid")] 167ShortName = "em")]
LightGbmMulticlassTrainer.cs (3)
88[Argument(ArgumentType.AtMostOnce, HelpText = "Use for multi-class classification when training data is not balanced", ShortName = "us")] 101[Argument(ArgumentType.AtMostOnce, HelpText = "Parameter for the sigmoid function.", ShortName = "sigmoid")] 110ShortName = "em")]
LightGbmRankingTrainer.cs (3)
131[Argument(ArgumentType.Multiple, HelpText = "An array of gains associated to each relevance label.", ShortName = "gains")] 138[Argument(ArgumentType.AtMostOnce, HelpText = "Parameter for the sigmoid function.", ShortName = "sigmoid")] 147ShortName = "em")]
LightGbmRegressionTrainer.cs (1)
137ShortName = "em")]
LightGbmTrainerBase.cs (14)
82[Argument(ArgumentType.AtMostOnce, HelpText = "Number of iterations.", SortOrder = 1, ShortName = "iter")] 95SortOrder = 2, ShortName = "lr", NullName = "<Auto>")] 104SortOrder = 2, ShortName = "nl", NullName = "<Auto>")] 113SortOrder = 2, ShortName = "mil", NullName = "<Auto>")] 124[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of bucket bin for features.", ShortName = "mb")] 142[Argument(ArgumentType.AtMostOnce, HelpText = "Verbose", ShortName = "v")] 157[Argument(ArgumentType.AtMostOnce, HelpText = "Number of parallel threads used to run LightGBM.", ShortName = "nt")] 167ShortName = "es")] 179[Argument(ArgumentType.AtMostOnce, HelpText = "Enable categorical split or not.", ShortName = "cat")] 186[Argument(ArgumentType.AtMostOnce, HelpText = "Enable special handling of missing value or not.", ShortName = "hmv")] 193[Argument(ArgumentType.AtMostOnce, HelpText = "Enable usage of zero (0) as missing value.", ShortName = "uzam")] 200[Argument(ArgumentType.AtMostOnce, HelpText = "Minimum number of instances per categorical group.", ShortName = "mdpg")] 208[Argument(ArgumentType.AtMostOnce, HelpText = "Max number of categorical thresholds.", ShortName = "maxcat")] 260[Argument(ArgumentType.Multiple, HelpText = "Parallel LightGBM Learning Algorithm", ShortName = "parag")]
Microsoft.ML.Maml (6)
ChainCommand.cs (1)
25[Argument(ArgumentType.Multiple, HelpText = "Command", Name = "Command", ShortName = "cmd", SignatureType = typeof(SignatureCommand))]
HelpCommand.cs (5)
44[Argument(ArgumentType.AtMostOnce, HelpText = "The kind of component to look for", ShortName = "kind")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "List the component kinds", ShortName = "list")] 50[Argument(ArgumentType.AtMostOnce, ShortName = "all", Hide = true)] 54[Argument(ArgumentType.Multiple, HelpText = "Extra DLLs", ShortName = "dll")] 436ShortName = "xml", Hide = true)]
Microsoft.ML.Mkl.Components (16)
OlsLinearRegression.cs (2)
82[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularization weight", ShortName = "l2", SortOrder = 50)] 90[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether to calculate per parameter significance statistics", ShortName = "sig")]
SymSgdClassificationTrainer.cs (9)
89"Multi-threading is not supported currently.", ShortName = "nt")] 95[Argument(ArgumentType.AtMostOnce, HelpText = "Number of passes over the data.", ShortName = "iter", SortOrder = 50)] 104[Argument(ArgumentType.AtMostOnce, HelpText = "Tolerance for difference in average loss in consecutive passes.", ShortName = "tol")] 110[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate", ShortName = "lr", NullName = "<Auto>", SortOrder = 51)] 118[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularization", ShortName = "l2", SortOrder = 52)] 128"global model. Low value means more updated global model and high value means less cache traffic.", ShortName = "freq", NullName = "<Auto>")] 136[Argument(ArgumentType.AtMostOnce, HelpText = "The acceleration memory budget in MB", ShortName = "accelMemBudget")] 142[Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data?", ShortName = "shuf")] 148[Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")]
VectorWhitening.cs (5)
54[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 63[Argument(ArgumentType.AtMostOnce, HelpText = "Max number of rows", ShortName = "rows")] 66[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to save inverse (recovery) matrix", ShortName = "saveInv")] 85[Argument(ArgumentType.AtMostOnce, HelpText = "Max number of rows", ShortName = "rows")] 88[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to save inverse (recovery) matrix", ShortName = "saveInv")]
Microsoft.ML.OnnxConverter (3)
SaveOnnxCommand.cs (3)
48[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of input column names to drop", ShortName = "idrop", SortOrder = 5)] 54[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of output column names to drop", ShortName = "odrop", SortOrder = 7)] 60[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Whether we should attempt to load the predictor and attach the scorer to the pipeline if one is present.", ShortName = "pred", SortOrder = 9)]
Microsoft.ML.OnnxTransformer (1)
OnnxTransform.cs (1)
73[Argument(ArgumentType.Required, HelpText = "Path to the onnx model file.", ShortName = "model", SortOrder = 0)]
Microsoft.ML.Parquet (6)
ParquetLoader.cs (2)
80[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of column chunk values to cache while reading from parquet file", ShortName = "chunkSize")] 83[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, will read large numbers as dates", ShortName = "bigIntDates")]
PartitionedFileLoader.cs (3)
71[Argument(ArgumentType.Required, HelpText = "Base path to the directory of your partitioned files.", ShortName = "bp")] 74[Argument(ArgumentType.AtMostOnce, HelpText = "Append a column with the file path.", ShortName = "path")] 77[Argument(ArgumentType.AtMostOnce, HelpText = "Path parser to extract column name/value pairs from the file path.", ShortName = "parser")]
PartitionedPathParser.cs (1)
81ShortName = "col", SortOrder = 1)]
Microsoft.ML.PCA (12)
PcaTrainer.cs (3)
96[Argument(ArgumentType.AtMostOnce, HelpText = "The number of components in the PCA", ShortName = "k", SortOrder = 50)] 106[Argument(ArgumentType.AtMostOnce, HelpText = "If enabled, data is centered to be zero mean", Name = "Center", ShortName = "center")] 110[Argument(ArgumentType.AtMostOnce, HelpText = "The seed for random number generation", ShortName = "seed")]
PcaTransformer.cs (9)
40[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 43[Argument(ArgumentType.Multiple, HelpText = "The name of the weight column", ShortName = "weight", Purpose = SpecialPurpose.ColumnName)] 46[Argument(ArgumentType.AtMostOnce, HelpText = "The number of components in the PCA", ShortName = "k")] 49[Argument(ArgumentType.AtMostOnce, HelpText = "Oversampling parameter for randomized PCA training", ShortName = "over")] 61[Argument(ArgumentType.Multiple, HelpText = "The name of the weight column", ShortName = "weight")] 64[Argument(ArgumentType.AtMostOnce, HelpText = "The number of components in the PCA", ShortName = "k")] 67[Argument(ArgumentType.AtMostOnce, HelpText = "Oversampling parameter for randomized PCA training", ShortName = "over")] 70[Argument(ArgumentType.AtMostOnce, HelpText = "If enabled, data is centered to be zero mean", ShortName = "center")] 73[Argument(ArgumentType.AtMostOnce, HelpText = "The seed for random number generation", ShortName = "seed")]
Microsoft.ML.Predictor.Tests (3)
CmdLine\CmdLine.cs (2)
177[Argument(ArgumentType.Required, ShortName = "r,r2")] 293[Argument(ArgumentType.AtMostOnce, ShortName = "val")]
CmdLine\CmdLineReverseTest.cs (1)
105[Argument(ArgumentType.Required, ShortName = "r")]
Microsoft.ML.Recommender (5)
MatrixFactorizationTrainer.cs (5)
195"This value is also known as the rank of matrix factorization because k is generally much smaller than m and n.", ShortName = "K")] 203[Argument(ArgumentType.AtMostOnce, HelpText = "Training iterations; that is, the times that the training algorithm iterates through the whole training data once.", ShortName = "iter,numiterations")] 216"Small value may increase the number of iterations needed to achieve a reasonable result. Large value may lead to numerical difficulty such as a infinity value.", ShortName = "Eta")] 256[Argument(ArgumentType.AtMostOnce, HelpText = "Number of threads can be used in the training procedure.", ShortName = "t,numthreads")] 268[Argument(ArgumentType.AtMostOnce, HelpText = "Force the factor matrices to be non-negative.", ShortName = "nn")]
Microsoft.ML.ResultProcessor (8)
ResultProcessor.cs (8)
312[Argument(ArgumentType.AtMostOnce, HelpText = "Output file name", ShortName = "o")] 316[Argument(ArgumentType.AtMostOnce, HelpText = "Output to a visualization HTML", ShortName = "html")] 320[Argument(ArgumentType.Multiple, HelpText = "Which metrics should be processed (default=all)?", ShortName = "a")] 324[Argument(ArgumentType.AtMostOnce, HelpText = "Include columns for standard deviations?", ShortName = "stdev")] 328[Argument(ArgumentType.AtMostOnce, HelpText = "Output per-fold results", ShortName = "opf")] 332[Argument(ArgumentType.AtMostOnce, HelpText = "Separator for per-fold results. Can be: actual char, 'tab', 'colon', 'space','comma'", ShortName = "opfsep")] 336[Argument(ArgumentType.Multiple, HelpText = "Extra DLLs", ShortName = "dll")] 341[Argument(ArgumentType.Multiple, HelpText = "Result file pattern with customized tag", ShortName = "in")]
Microsoft.ML.StandardTrainers (78)
FactorizationMachine\FactorizationMachineTrainer.cs (10)
111[Argument(ArgumentType.AtMostOnce, HelpText = "Initial learning rate", ShortName = "lr", SortOrder = 1)] 118[Argument(ArgumentType.AtMostOnce, HelpText = "Number of training iterations", ShortName = "iters,iter", SortOrder = 2)] 125[Argument(ArgumentType.AtMostOnce, HelpText = "Latent space dimension", ShortName = "d", SortOrder = 3)] 132[Argument(ArgumentType.AtMostOnce, HelpText = "Regularization coefficient of linear weights", ShortName = "lambdaLinear", SortOrder = 4)] 139[Argument(ArgumentType.AtMostOnce, HelpText = "Regularization coefficient of latent weights", ShortName = "lambdaLatent", SortOrder = 5)] 146[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to normalize the input vectors so that the concatenation of all fields' feature vectors is unit-length", ShortName = "norm", SortOrder = 6)] 155ShortName = "exfeat", SortOrder = 7)] 161[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to shuffle for each training iteration", ShortName = "shuf", SortOrder = 90)] 167[Argument(ArgumentType.AtMostOnce, HelpText = "Report traning progress or not", ShortName = "verbose", SortOrder = 91)] 173[Argument(ArgumentType.AtMostOnce, HelpText = "Radius of initial latent factors", ShortName = "rad", SortOrder = 110)]
LdSvm\LdSvmTrainer.cs (7)
78[Argument(ArgumentType.AtMostOnce, HelpText = "Depth of Local Deep SVM tree", ShortName = "depth", SortOrder = 50)] 87[Argument(ArgumentType.AtMostOnce, HelpText = "Regularizer for classifier parameter W", ShortName = "lw", SortOrder = 50)] 96[Argument(ArgumentType.AtMostOnce, HelpText = "Regularizer for kernel parameter Theta", ShortName = "lt", SortOrder = 50)] 105[Argument(ArgumentType.AtMostOnce, HelpText = "Regularizer for kernel parameter Thetaprime", ShortName = "lp", SortOrder = 50)] 114[Argument(ArgumentType.AtMostOnce, HelpText = "Parameter for sigmoid sharpness", ShortName = "s", SortOrder = 50)] 123[Argument(ArgumentType.AtMostOnce, HelpText = "No bias", ShortName = "bias")] 132HelpText = "Number of iterations", ShortName = "iter,NumIterations", SortOrder = 50)]
Standard\LogisticRegression\LbfgsPredictorBase.cs (12)
45[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularization weight", ShortName = "l2, L2Weight", SortOrder = 50)] 54[Argument(ArgumentType.AtMostOnce, HelpText = "L1 regularization weight", ShortName = "l1, L1Weight", SortOrder = 50)] 64ShortName = "ot, OptTol", SortOrder = 50)] 73[Argument(ArgumentType.AtMostOnce, HelpText = "Memory size for L-BFGS. Low=faster, less accurate", ShortName = "m, MemorySize", SortOrder = 50)] 82[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum iterations.", ShortName = "maxiter, MaxIterations, NumberOfIterations")] 92ShortName = "sgd, SgdInitializationTolerance")] 102ShortName = "q")] 112[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Init weights diameter", ShortName = "initwts, InitWtsDiameter", SortOrder = 140)] 120ShortName = "t", Hide = true)] 126[Argument(ArgumentType.AtMostOnce, HelpText = "Number of threads", ShortName = "nt, NumThreads")] 132[Argument(ArgumentType.AtMostOnce, HelpText = "Force densification of the internal optimization vectors", ShortName = "do")] 140[Argument(ArgumentType.AtMostOnce, HelpText = "Enforce non-negative weights", ShortName = "nn", SortOrder = 90)]
Standard\LogisticRegression\LogisticRegression.cs (1)
105[Argument(ArgumentType.AtMostOnce, HelpText = "Show statistics of training examples.", ShortName = "stat, ShowTrainingStats", SortOrder = 50)]
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
106[Argument(ArgumentType.AtMostOnce, HelpText = "Show statistics of training examples.", ShortName = "stat, ShowTrainingStats", SortOrder = 50)]
Standard\MulticlassClassification\MetaMulticlassTrainer.cs (4)
23[Argument(ArgumentType.Multiple, HelpText = "Base predictor", ShortName = "p", SortOrder = 4, SignatureType = typeof(SignatureBinaryClassifierTrainer))] 27[Argument(ArgumentType.Multiple, HelpText = "Output calibrator", ShortName = "cali", SortOrder = 150, NullName = "<None>", SignatureType = typeof(SignatureCalibrator))] 30[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of instances to train the calibrator", SortOrder = 150, ShortName = "numcali")] 33[Argument(ArgumentType.Multiple, HelpText = "Whether to treat missing labels as having negative labels, or exclude their rows from dataview.", SortOrder = 150, ShortName = "missNeg")]
Standard\MulticlassClassification\OneVersusAllTrainer.cs (1)
105[Argument(ArgumentType.AtMostOnce, HelpText = "Use probability or margins to determine max", ShortName = "useprob")]
Standard\Online\AveragedLinear.cs (9)
27[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate", ShortName = "lr", SortOrder = 50)] 40[Argument(ArgumentType.AtMostOnce, HelpText = "Decrease learning rate", ShortName = "decreaselr", SortOrder = 50)] 52[Argument(ArgumentType.AtMostOnce, HelpText = "Number of examples after which weights will be reset to the current average", ShortName = "numreset")] 63[Argument(ArgumentType.AtMostOnce, HelpText = "Instead of updating averaged weights on every example, only update when loss is nonzero", ShortName = "lazy,DoLazyUpdates")] 69[Argument(ArgumentType.AtMostOnce, HelpText = "L2 Regularization Weight", ShortName = "reg,L2RegularizerWeight", SortOrder = 50)] 81[Argument(ArgumentType.AtMostOnce, HelpText = "Extra weight given to more recent updates", ShortName = "rg")] 92[Argument(ArgumentType.AtMostOnce, HelpText = "Whether Recency Gain is multiplicative (vs. additive)", ShortName = "rgm,RecencyGainMulti")] 102[Argument(ArgumentType.AtMostOnce, HelpText = "Do averaging?", ShortName = "avg")] 108[Argument(ArgumentType.AtMostOnce, HelpText = "The inexactness tolerance for averaging", ShortName = "avgtol")]
Standard\Online\AveragedPerceptron.cs (1)
99[Argument(ArgumentType.Multiple, Name = "LossFunction", HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)]
Standard\Online\LinearSvm.cs (4)
83[Argument(ArgumentType.AtMostOnce, HelpText = "Regularizer constant", ShortName = "lambda", SortOrder = 50)] 89[Argument(ArgumentType.AtMostOnce, HelpText = "Batch size", ShortName = "batch", SortOrder = 190)] 94[Argument(ArgumentType.AtMostOnce, HelpText = "Perform projection to unit-ball? Typically used with batch size > 1.", ShortName = "project", SortOrder = 50)] 113[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight,WeightColumn", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
Standard\Online\OnlineGradientDescent.cs (1)
72[Argument(ArgumentType.Multiple, Name = "LossFunction", HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)]
Standard\Online\OnlineLinear.cs (4)
27[Argument(ArgumentType.AtMostOnce, HelpText = "Number of iterations", ShortName = "iter,numIterations", SortOrder = 50)] 36[Argument(ArgumentType.AtMostOnce, HelpText = "Initial Weights and bias, comma-separated", ShortName = "initweights")] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Init weights diameter", ShortName = "initwts,initWtsDiameter", SortOrder = 140)] 60[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to shuffle for each training iteration", ShortName = "shuf")]
Standard\SdcaBinary.cs (21)
163[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularizer constant. By default the l2 constant is automatically inferred based on data set.", NullName = "<Auto>", ShortName = "l2, L2Const", SortOrder = 1)] 174NullName = "<Auto>", Name = "L1Threshold", ShortName = "l1", SortOrder = 2)] 186[Argument(ArgumentType.AtMostOnce, HelpText = "Degree of lock-free parallelism. Defaults to automatic. Determinism not guaranteed.", NullName = "<Auto>", ShortName = "nt,t,threads, NumThreads", SortOrder = 50)] 193[Argument(ArgumentType.AtMostOnce, HelpText = "The tolerance for the ratio between duality gap and primal loss for convergence checking.", ShortName = "tol")] 205[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of iterations; set to 1 to simulate online learning. Defaults to automatic.", NullName = "<Auto>", ShortName = "iter, MaxIterations, NumberOfIterations")] 218[Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")] 228[Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Set as negative or zero for not checking at all. If left blank, it defaults to check after every 'numThreads' iterations.", NullName = "<Auto>", ShortName = "checkFreq, CheckFrequency")] 234[Argument(ArgumentType.AtMostOnce, HelpText = "The learning rate for adjusting bias from being regularized.", ShortName = "blr")] 1472[Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")] 1690[Argument(ArgumentType.Multiple, Name = "LossFunction", HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)] 1762[Argument(ArgumentType.Multiple, HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)] 1840[Argument(ArgumentType.AtMostOnce, HelpText = "L2 Regularization constant", ShortName = "l2, L2Weight", SortOrder = 50)] 1852[Argument(ArgumentType.AtMostOnce, HelpText = "Degree of lock-free parallelism. Defaults to automatic depending on data sparseness. Determinism not guaranteed.", ShortName = "nt,t,threads, NumThreads", SortOrder = 50)] 1860[Argument(ArgumentType.AtMostOnce, HelpText = "Exponential moving averaged improvement tolerance for convergence", ShortName = "tol")] 1872[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of iterations; set to 1 to simulate online learning.", ShortName = "iter, MaxIterations")] 1881[Argument(ArgumentType.AtMostOnce, HelpText = "Initial learning rate (only used by SGD)", Name = "InitialLearningRate", ShortName = "ilr,lr,InitLearningRate")] 1893[Argument(ArgumentType.AtMostOnce, HelpText = "Shuffle data every epoch?", ShortName = "shuf")] 1903[Argument(ArgumentType.AtMostOnce, HelpText = "Apply weight to the positive class, for imbalanced data", ShortName = "piw")] 1912[Argument(ArgumentType.AtMostOnce, HelpText = "Convergence check frequency (in terms of number of iterations). Default equals number of threads", ShortName = "checkFreq")] 2362[Argument(ArgumentType.Multiple, HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)] 2415[Argument(ArgumentType.Multiple, HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)]
Standard\SdcaMulticlass.cs (1)
99[Argument(ArgumentType.Multiple, Name = "LossFunction", HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)]
Standard\SdcaRegression.cs (1)
72[Argument(ArgumentType.Multiple, Name = "LossFunction", HelpText = "Loss Function", ShortName = "loss", SortOrder = 50)]
Microsoft.ML.Sweeper (56)
Algorithms\Grid.cs (3)
32[Argument(ArgumentType.Multiple, HelpText = "Swept parameters", ShortName = "p", SignatureType = typeof(SignatureSweeperParameter))] 35[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of tries to generate distinct parameter sets.", ShortName = "r")] 116[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Limit for the number of combinations to generate the entire grid.", ShortName = "maxpoints")]
Algorithms\KdoSweeper.cs (10)
41[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Swept parameters", ShortName = "p", SignatureType = typeof(SignatureSweeperParameter))] 44[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random number generator for the first batch sweeper", ShortName = "seed")] 47[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If iteration point is outside parameter definitions, should it be projected?", ShortName = "project")] 50[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of points to use for random initialization", ShortName = "nip")] 53[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum mutation spread", ShortName = "mms")] 56[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Maximum length of history to retain", ShortName = "hlen")] 59[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If true, draws samples from independent Beta distributions, rather than multivariate Gaussian", ShortName = "beta")] 65[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Proportion of trials, between 0 and 1, that are uniform random draws", ShortName = "prand")] 68[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Maximum power for rescaling (the larger the number, the stronger the exploitation of good points)", ShortName = "wrp")] 74[Argument(ArgumentType.LastOccurrenceWins, HelpText = "(Deprecated) Use legacy discrete parameter behavior.", ShortName = "legacy", Hide = true, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)]
Algorithms\NelderMead.cs (10)
23[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Swept parameters", ShortName = "p", SignatureType = typeof(SignatureSweeperParameter))] 26[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The sweeper used to get the initial results.", ShortName = "init", SignatureType = typeof(SignatureSweeperFromParameterList))] 29[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random number generator for the first batch sweeper", ShortName = "seed")] 32[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Simplex diameter for stopping", ShortName = "dstop")] 36HelpText = "If iteration point is outside parameter definitions, should it be projected?", ShortName = "project")] 40[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Reflection parameter", ShortName = "dr")] 43[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Expansion parameter", ShortName = "de")] 46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Inside contraction parameter", ShortName = "dic")] 49[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Outside contraction parameter", ShortName = "doc")] 52[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Shrinkage parameter", ShortName = "ds")]
Algorithms\SmacSweeper.cs (11)
28[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Swept parameters", ShortName = "p", SignatureType = typeof(SignatureSweeperParameter))] 31[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random number generator for the first batch sweeper", ShortName = "seed")] 34[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If iteration point is outside parameter definitions, should it be projected?", ShortName = "project")] 37[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of regression trees in forest", ShortName = "numtrees")] 40[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum number of data points required to be in a node if it is to be split further", ShortName = "nmin")] 43[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of points to use for random initialization", ShortName = "nip")] 46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of search parents to use for local search in maximizing EI acquisition function", ShortName = "lsp")] 49[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of random configurations when maximizing EI acquisition function", ShortName = "nrcan")] 52[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Fraction of eligible dimensions to split on (i.e., split ratio)", ShortName = "sr")] 55[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Epsilon threshold for ending local searches", ShortName = "eps")] 58[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of neighbors to sample for locally searching each numerical parameter", ShortName = "nnnp")]
AsyncSweeper.cs (4)
155[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Base sweeper", ShortName = "sweeper", SignatureType = typeof(SignatureSweeper))] 158[Argument(ArgumentType.AtMostOnce, HelpText = "Sweep batch size", ShortName = "batchsize")] 161[Argument(ArgumentType.AtMostOnce, HelpText = "Synchronization relaxation", ShortName = "relaxation")] 164[Argument(ArgumentType.AtMostOnce, HelpText = "Random seed", ShortName = "seed")]
ConfigRunner.cs (5)
35[Argument(ArgumentType.AtMostOnce, HelpText = "Command pattern for the sweeps", ShortName = "pattern")] 38[Argument(ArgumentType.AtMostOnce, HelpText = "output folder for the outputs of the sweeps", ShortName = "outfolder")] 41[Argument(ArgumentType.AtMostOnce, HelpText = "prefix to add to the output file names", ShortName = "pre")] 47[Argument(ArgumentType.Multiple, HelpText = "Specify how to extract the metrics from the result file.", ShortName = "ev", SignatureType = typeof(SignatureSweepResultEvaluator))] 185[Argument(ArgumentType.AtMostOnce, HelpText = "The number of threads to use for the sweep (default auto determined by the number of cores)", ShortName = "t")]
Parameters.cs (5)
29[Argument(ArgumentType.Required, HelpText = "Parameter name", ShortName = "n")] 35[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Number of steps for grid runthrough.", ShortName = "steps")] 38[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Amount of increment between steps (multiplicative if log).", ShortName = "inc")] 41[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Log scale.", ShortName = "log")] 65[Argument(ArgumentType.Multiple, HelpText = "Values", ShortName = "v")]
SweepCommand.cs (6)
26[Argument(ArgumentType.Multiple, HelpText = "Config runner", ShortName = "run,ev,evaluator", SignatureType = typeof(SignatureConfigRunner))] 30[Argument(ArgumentType.Multiple, HelpText = "Sweeper", ShortName = "s", SignatureType = typeof(SignatureSweeper))] 33[Argument(ArgumentType.AtMostOnce, HelpText = "Initial Sweep batch size (for instantiating sweep algorithm)", ShortName = "isbs")] 36[Argument(ArgumentType.AtMostOnce, HelpText = "Sweep batch size", ShortName = "sbs")] 39[Argument(ArgumentType.AtMostOnce, HelpText = "Sweep number of batches", ShortName = "snb")] 42[Argument(ArgumentType.AtMostOnce, HelpText = "Random seed", ShortName = "seed")]
SweepResultEvaluator.cs (1)
23[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The sweeper used to get the initial results.", ShortName = "m")]
SynthConfigRunner.cs (1)
27[Argument(ArgumentType.AtMostOnce, HelpText = "The number of threads to use for the sweep (default auto determined by the number of cores)", ShortName = "t")]
Microsoft.ML.TensorFlow (2)
TensorflowTransform.cs (2)
943[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "The names of the model inputs", ShortName = "inputs", SortOrder = 1)] 949[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "The name of the outputs", ShortName = "outputs", SortOrder = 2)]
Microsoft.ML.TimeSeries (93)
ExponentialAverageTransform.cs (3)
33[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 37[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 42ShortName = "d", SortOrder = 4)]
IidChangePointDetector.cs (5)
40[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 48[Argument(ArgumentType.AtMostOnce, HelpText = "The length of the sliding window on p-values for computing the martingale score.", ShortName = "wnd", 53ShortName = "cnf", SortOrder = 3)] 56[Argument(ArgumentType.AtMostOnce, HelpText = "The martingale used for scoring.", ShortName = "mart", SortOrder = 103)] 60ShortName = "eps", SortOrder = 104)]
IidSpikeDetector.cs (4)
39[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 47[Argument(ArgumentType.AtMostOnce, HelpText = "The argument that determines whether to detect positive or negative anomalies, or both.", ShortName = "side", 51[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the p-value.", ShortName = "wnd", 56ShortName = "cnf", SortOrder = 3)]
MovingAverageTransform.cs (5)
32[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 36[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 40[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the moving average", ShortName = "wnd", SortOrder = 3)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "Lag between current observation and last observation from the sliding window", ShortName = "l", SortOrder = 4)] 48ShortName = "w", SortOrder = 5)]
PercentileThresholdTransform.cs (4)
33[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 37[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 41[Argument(ArgumentType.AtMostOnce, HelpText = "The percentile value for thresholding in the range [0, 100]", ShortName = "pcnt", 46"The default value is set to 1.", ShortName = "wnd",
PValueTransform.cs (6)
33[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 37[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 41[Argument(ArgumentType.AtMostOnce, HelpText = "The seed value of the random generator", ShortName = "seed", 45[Argument(ArgumentType.AtMostOnce, HelpText = "The flag that determines whether the p-values are calculated on the positive side", ShortName = "pos", 49[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the p-value", ShortName = "wnd", 54ShortName = "initwnd", SortOrder = 6)]
SequentialAnomalyDetectionTransformBase.cs (9)
78[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 82[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 86[Argument(ArgumentType.AtMostOnce, HelpText = "The argument that determines whether to detect positive or negative anomalies, or both", ShortName = "side", 90[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the p-value.", ShortName = "wnd", 95ShortName = "initwnd", SortOrder = 5)] 99ShortName = "martingale", SortOrder = 6)] 103ShortName = "alert", SortOrder = 7)] 107ShortName = "eps", SortOrder = 8)] 111ShortName = "thr", SortOrder = 9)]
SequentialForecastingTransformBase.cs (6)
21[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 25[Argument(ArgumentType.Required, HelpText = "The name of the new column", ShortName = "name", 29[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", 33[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", 37[Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the beginning used for training.", ShortName = "wnd", 42"is set to 0, which means there is no initial window considered.", ShortName = "initwnd", SortOrder = 5)]
SlidingWindowTransformBase.cs (3)
41[Argument(ArgumentType.Required, HelpText = "The name of the source column", ShortName = "src", 49[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the moving average", ShortName = "wnd", SortOrder = 3)] 52[Argument(ArgumentType.AtMostOnce, HelpText = "Lag between current observation and last observation from the sliding window", ShortName = "l", SortOrder = 4)]
SRCNNAnomalyDetector.cs (7)
39[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 47[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing spectral residual", ShortName = "wnd", 52ShortName = "backwnd", SortOrder = 102)] 56ShortName = "aheadwnd", SortOrder = 103)] 60ShortName = "avgwnd", SortOrder = 104)] 64ShortName = "jdgwnd", SortOrder = 105)] 68ShortName = "thre", SortOrder = 106)]
SrCnnEntireAnomalyDetector.cs (6)
60SortOrder = 3, ShortName = "thr")] 64SortOrder = 4, ShortName = "bsz")] 68SortOrder = 4, ShortName = "sen")] 72SortOrder = 5, ShortName = "dtmd")] 76SortOrder = 5, ShortName = "prd")] 80SortOrder = 6, ShortName = "dsmd")]
SrCnnTransformBase.cs (8)
17[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 25[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing spectral residual", ShortName = "wnd", 29[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the initial window for computing. The default value is set to 0, which means there is no initial window considered.", ShortName = "iwnd", 34ShortName = "backwnd", SortOrder = 5)] 38ShortName = "aheadwnd", SortOrder = 6)] 42ShortName = "avgwnd", SortOrder = 7)] 46ShortName = "jdgwnd", SortOrder = 8)] 50ShortName = "thre", SortOrder = 9)]
SsaAnomalyDetectionBase.cs (4)
152[Argument(ArgumentType.Required, HelpText = "The inner window size for SSA in [2, windowSize]", ShortName = "swnd", SortOrder = 11)] 155[Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0, 1]", ShortName = "disc", SortOrder = 12)] 158[Argument(ArgumentType.AtMostOnce, HelpText = "The function used to compute the error between the expected and the observed value", ShortName = "err", SortOrder = 13)] 161[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determing whether the model is adaptive", ShortName = "adp", SortOrder = 14)]
SsaChangePointDetector.cs (8)
40[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 48[Argument(ArgumentType.AtMostOnce, HelpText = "The length of the sliding window on p-values for computing the martingale score.", ShortName = "wnd", 53ShortName = "twnd", SortOrder = 3)] 57ShortName = "cnf", SortOrder = 4)] 60[Argument(ArgumentType.Required, HelpText = "An upper bound on the largest relevant seasonality in the input time-series.", ShortName = "swnd", SortOrder = 5)] 63[Argument(ArgumentType.AtMostOnce, HelpText = "The function used to compute the error between the expected and the observed value.", ShortName = "err", SortOrder = 103)] 66[Argument(ArgumentType.AtMostOnce, HelpText = "The martingale used for scoring.", ShortName = "mart", SortOrder = 104)] 70ShortName = "eps", SortOrder = 105)]
SSaForecasting.cs (5)
38[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 44[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)] 47[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)] 50[Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)] 53[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determing whether the model is adaptive", ShortName = "adp", SortOrder = 6)]
SsaForecastingBase.cs (3)
85[Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0, 1]", ShortName = "disc", SortOrder = 12)] 88[Argument(ArgumentType.AtMostOnce, HelpText = "The function used to compute the error between the expected and the observed value", ShortName = "err", SortOrder = 13)] 91[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determing whether the model is adaptive", ShortName = "adp", SortOrder = 14)]
SsaSpikeDetector.cs (7)
39[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", 47[Argument(ArgumentType.AtMostOnce, HelpText = "The argument that determines whether to detect positive or negative anomalies, or both.", ShortName = "side", 51[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the sliding window for computing the p-value.", ShortName = "wnd", 56ShortName = "twnd", SortOrder = 3)] 60ShortName = "cnf", SortOrder = 4)] 63[Argument(ArgumentType.Required, HelpText = "An upper bound on the largest relevant seasonality in the input time-series.", ShortName = "swnd", SortOrder = 5)] 66[Argument(ArgumentType.AtMostOnce, HelpText = "The function used to compute the error between the expected and the observed value.", ShortName = "err", SortOrder = 103)]
Microsoft.ML.Transforms (213)
CountFeatureSelection.cs (2)
83[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", Name = "Column", ShortName = "col", SortOrder = 1)] 86[Argument(ArgumentType.Required, HelpText = "If the count of non-default values for a slot is greater than or equal to this threshold, the slot is preserved", ShortName = "c", SortOrder = 1)]
Dracula\CMCountTable.cs (2)
182[Argument(ArgumentType.AtMostOnce, HelpText = "Count-Min Sketch table depth", ShortName = "d")] 185[Argument(ArgumentType.AtMostOnce, HelpText = "Count-Min Sketch width", ShortName = "w")]
Dracula\CountTableTransformer.cs (12)
356[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)] 359[Argument(ArgumentType.Multiple, HelpText = "Count table settings", ShortName = "table", SignatureType = typeof(SignatureCountTableBuilder))] 362[Argument(ArgumentType.AtMostOnce, HelpText = "The coefficient with which to apply the prior smoothing to the features", ShortName = "prior")] 365[Argument(ArgumentType.AtMostOnce, HelpText = "Laplacian noise diversity/scale-parameter. Suggest keeping it less than 1.", ShortName = "laplace")] 368[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random generator for the laplacian noise.", ShortName = "seed")] 371[Argument(ArgumentType.Required, HelpText = "Label column", ShortName = "label,lab", Purpose = SpecialPurpose.ColumnName)] 374[Argument(ArgumentType.AtMostOnce, HelpText = "Optional model file to load counts from. If this is specified all other options are ignored.", ShortName = "inmodel, extfile")] 377[Argument(ArgumentType.AtMostOnce, HelpText = "Keep counts for all columns in one shared count table", ShortName = "shared")] 383[Argument(ArgumentType.Multiple, HelpText = "Count table settings", ShortName = "table", SignatureType = typeof(SignatureCountTableBuilder))] 386[Argument(ArgumentType.AtMostOnce, HelpText = "The coefficient with which to apply the prior smoothing to the features", ShortName = "prior")] 389[Argument(ArgumentType.AtMostOnce, HelpText = "Laplacian noise diversity/scale-parameter. Suggest keeping it less than 1.", ShortName = "laplace")] 392[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random generator for the laplacian noise.", ShortName = "seed")]
Dracula\CountTargetEncodingTransformer.cs (13)
57ShortName = "col", SortOrder = 1)] 60[Argument(ArgumentType.Multiple, HelpText = "Count table settings", ShortName = "table", SignatureType = typeof(SignatureCountTableBuilder))] 63[Argument(ArgumentType.AtMostOnce, HelpText = "The coefficient with which to apply the prior smoothing to the features", ShortName = "prior")] 66[Argument(ArgumentType.AtMostOnce, HelpText = "Laplacian noise diversity/scale-parameter. Suggest keeping it less than 1.", ShortName = "laplace")] 69[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random generator for the laplacian noise.", ShortName = "seed")] 72[Argument(ArgumentType.Required, HelpText = "Label column", ShortName = "label,lab", Purpose = SpecialPurpose.ColumnName)] 75[Argument(ArgumentType.AtMostOnce, HelpText = "Optional model file to load counts from. If this is specified all other options are ignored.", ShortName = "inmodel, extfile")] 78[Argument(ArgumentType.AtMostOnce, HelpText = "Keep counts for all columns in one shared count table", ShortName = "shared")] 85ShortName = "bits")] 94[Argument(ArgumentType.Multiple, HelpText = "Count table settings", ShortName = "table", SignatureType = typeof(SignatureCountTableBuilder))] 97[Argument(ArgumentType.AtMostOnce, HelpText = "The coefficient with which to apply the prior smoothing to the features", ShortName = "prior")] 100[Argument(ArgumentType.AtMostOnce, HelpText = "Laplacian noise diversity/scale-parameter. Suggest keeping it less than 1.", ShortName = "laplace")] 103[Argument(ArgumentType.AtMostOnce, HelpText = "Seed for the random generator for the laplacian noise.", ShortName = "seed")]
Dracula\DictCountTable.cs (1)
142[Argument(ArgumentType.AtMostOnce, HelpText = "Garbage threshold (counts below or equal to the threshold are assigned to the garbage bin)", ShortName = "gb")]
ExpressionTransformer.cs (3)
216[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s)", ShortName = "col", SortOrder = 1)] 219[Argument(ArgumentType.AtMostOnce, ShortName = "expr", SortOrder = 2, HelpText = "Lambda expression which will be applied.")] 225[Argument(ArgumentType.AtMostOnce, ShortName = "expr", SortOrder = 2, HelpText = "Lambda expression which will be applied.")]
FourierDistributionSampler.cs (1)
84[Argument(ArgumentType.AtMostOnce, HelpText = "gamma in the kernel definition: exp(-gamma*||x-y||^2 / r^2). r is an estimate of the average intra-example distance", ShortName = "g")]
GcnTransform.cs (5)
45[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 48[Argument(ArgumentType.AtMostOnce, HelpText = "The norm to use to normalize each sample", ShortName = "norm", SortOrder = 1)] 57[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 63[Argument(ArgumentType.AtMostOnce, HelpText = "Normalize by standard deviation rather than L2 norm", ShortName = "useStd")] 90[Argument(ArgumentType.AtMostOnce, HelpText = "The norm to use to normalize each sample", ShortName = "norm", SortOrder = 1)]
GroupTransform.cs (2)
87[Argument(ArgumentType.Multiple, HelpText = "Columns to group by", Name = "GroupKey", ShortName = "g", SortOrder = 1, 92[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to group together", Name = "Column", ShortName = "col", SortOrder = 2)]
HashJoiningTransform.cs (5)
51ShortName = "col", 59ShortName = "bits", SortOrder = 2)] 65[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")] 79[Argument(ArgumentType.AtMostOnce, HelpText = "Number of bits to hash into. Must be between 1 and 31, inclusive.", ShortName = "bits")] 85[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")]
KeyToVectorMapping.cs (1)
38Name = "Column", ShortName = "col", SortOrder = 1)]
LearnerFeatureSelection.cs (10)
32[Argument(ArgumentType.LastOccurrenceWins, HelpText = "If the corresponding absolute value of the weight for a slot is greater than this threshold, the slot is preserved", ShortName = "ft", SortOrder = 2)] 35[Argument(ArgumentType.AtMostOnce, HelpText = "The number of slots to preserve", ShortName = "topk", SortOrder = 1)] 40[Argument(ArgumentType.Multiple, HelpText = "Filter", ShortName = "f", SortOrder = 1, SignatureType = typeof(SignatureFeatureScorerTrainer))] 46[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for features", ShortName = "feat,col", SortOrder = 3, Purpose = SpecialPurpose.ColumnName)] 49[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 4, Purpose = SpecialPurpose.ColumnName)] 52[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 5, Purpose = SpecialPurpose.ColumnName)] 55[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for grouping", ShortName = "group", Purpose = SpecialPurpose.ColumnName)] 58[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name", Purpose = SpecialPurpose.ColumnName)] 65[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Normalize option for the feature column", ShortName = "norm")] 68[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Whether we should cache input training data", ShortName = "cache")]
LoadTransform.cs (2)
31[Argument(ArgumentType.Required, HelpText = "Model file to load the transforms from", ShortName = "in", 39[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to load all transforms except those marked by tags", ShortName = "comp", SortOrder = 3)]
MissingValueDroppingTransformer.cs (1)
63[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to drop the NAs for", Name = "Column", ShortName = "col", SortOrder = 1)]
MissingValueHandlingTransformer.cs (6)
59[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:rep:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 62[Argument(ArgumentType.AtMostOnce, HelpText = "The replacement method to utilize", ShortName = "kind", SortOrder = 2)] 68[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to impute values by slot", ShortName = "slot")] 71[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not to concatenate an indicator vector column to the value column", ShortName = "ind")] 82[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to impute values by slot", ShortName = "slot")] 85[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not to concatenate an indicator vector column to the value column", ShortName = "ind")]
MissingValueIndicatorTransform.cs (1)
45[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
MissingValueIndicatorTransformer.cs (1)
57[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
MissingValueReplacing.cs (4)
78[Argument(ArgumentType.AtMostOnce, HelpText = "Replacement value for NAs (uses default value if not given)", ShortName = "rep")] 118[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:rep:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 121[Argument(ArgumentType.AtMostOnce, HelpText = "The replacement method to utilize", ShortName = "kind")] 125[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to impute values by slot", ShortName = "slot")]
MutualInformationFeatureSelection.cs (4)
91[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", Name = "Column", ShortName = "col", SortOrder = 1)] 94[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab", 98[Argument(ArgumentType.AtMostOnce, HelpText = "The maximum number of slots to preserve in output", ShortName = "topk,numSlotsToKeep", 103ShortName = "bins")]
OneHotEncoding.cs (3)
32[Argument(ArgumentType.AtMostOnce, HelpText = "Output kind: Bag (multi-set vector), Ind (indicator vector), Key (index), or Binary encoded indicator vector", ShortName = "kind")] 74[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 78ShortName = "kind", SortOrder = 102)]
OneHotHashEncoding.cs (9)
29ShortName = "bits")] 35[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")] 40ShortName = "ih")] 44ShortName = "kind", SortOrder = 102)] 91[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:numberOfBits:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 95ShortName = "bits", SortOrder = 2)] 101[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each term should be included in the hash", ShortName = "ord")] 106ShortName = "ih")] 110ShortName = "kind", SortOrder = 102)]
OptionalColumnTransform.cs (1)
37[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)]
ProduceIdTransform.cs (1)
33[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the column to produce", ShortName = "col", SortOrder = 1)]
RandomFourierFeaturizing.cs (5)
38[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 41[Argument(ArgumentType.AtMostOnce, HelpText = "The number of random Fourier features to create", ShortName = "dim")] 44[Argument(ArgumentType.Multiple, HelpText = "Which kernel to use?", ShortName = "kernel", SignatureType = typeof(SignatureKernelBase))] 58[Argument(ArgumentType.AtMostOnce, HelpText = "The number of random Fourier features to create", ShortName = "dim")] 61[Argument(ArgumentType.Multiple, HelpText = "which kernel to use?", ShortName = "kernel", SignatureType = typeof(SignatureKernelBase))]
SvmLight\SvmLightLoader.cs (3)
88[Argument(ArgumentType.AtMostOnce, HelpText = "The size of the feature vectors.", ShortName = "size")] 91[Argument(ArgumentType.Multiple, HelpText = "Whether the features are indexed by numbers starting at 0, by numbers starting at 1, or by feature names.", ShortName = "indices")] 94[Argument(ArgumentType.AtMostOnce, HelpText = "The number of rows used to train the feature name to index mapping transform. If unspecified, all rows will be used.", ShortName = "numxf")]
SvmLight\SvmLightSaver.cs (6)
31[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Write the variant of SVM-light format where feature indices start from 0, not 1", ShortName = "z")] 34[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Format output labels for a binary classification problem (-1 for negative, 1 for positive)", ShortName = "b")] 37[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for features", ShortName = "feat", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 40[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for labels", ShortName = "lab", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example weight", ShortName = "weight", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 46[Argument(ArgumentType.AtMostOnce, HelpText = "Column to use for example groupId", ShortName = "groupId", SortOrder = 5, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
Text\LdaTransform.cs (17)
56[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", Name = "Column", ShortName = "col", SortOrder = 49)] 79[Argument(ArgumentType.AtMostOnce, HelpText = "Number of iterations", ShortName = "iter")] 84[Argument(ArgumentType.AtMostOnce, HelpText = "Compute log likelihood over local dataset on this iteration interval", ShortName = "llInterval")] 88[Argument(ArgumentType.AtMostOnce, HelpText = "The number of training threads. Default value depends on number of logical processors.", ShortName = "t", SortOrder = 50)] 91[Argument(ArgumentType.AtMostOnce, HelpText = "The threshold of maximum count of tokens per doc", ShortName = "maxNumToken", SortOrder = 50)] 94[Argument(ArgumentType.AtMostOnce, HelpText = "The number of words to summarize the topic", ShortName = "ns")] 97[Argument(ArgumentType.AtMostOnce, HelpText = "The number of burn-in iterations", ShortName = "burninIter")] 102[Argument(ArgumentType.AtMostOnce, HelpText = "Reset the random number generator for each document", ShortName = "reset")] 105[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to output the topic-word summary in text format when saving the model to disk", ShortName = "summary")] 123[Argument(ArgumentType.AtMostOnce, HelpText = "Number of iterations", ShortName = "iter")] 126[Argument(ArgumentType.AtMostOnce, HelpText = "Compute log likelihood over local dataset on this iteration interval", ShortName = "llInterval")] 129[Argument(ArgumentType.AtMostOnce, HelpText = "The number of training threads", ShortName = "t")] 132[Argument(ArgumentType.AtMostOnce, HelpText = "The threshold of maximum count of tokens per doc", ShortName = "maxNumToken")] 135[Argument(ArgumentType.AtMostOnce, HelpText = "The number of words to summarize the topic", ShortName = "ns")] 138[Argument(ArgumentType.AtMostOnce, HelpText = "The number of burn-in iterations", ShortName = "burninIter")] 141[Argument(ArgumentType.AtMostOnce, HelpText = "Reset the random number generator for each document", ShortName = "reset")] 144[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to output the topic-word summary in text format when saving the model to disk", ShortName = "summary")]
Text\NgramHashingTransformer.cs (15)
37[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum n-gram length", ShortName = "ngram")] 41"Whether to include all n-gram lengths up to " + nameof(NgramLength) + " or only " + nameof(NgramLength), Name = "AllLengths", ShortName = "all")] 46ShortName = "skips")] 51Name = "HashBits", ShortName = "bits")] 57[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to rehash unigrams", ShortName = "rehash")] 60[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each source column should be included in the hash (when there are multiple source columns).", ShortName = "ord")] 64ShortName = "ih")] 113ShortName = "col", 117[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum n-gram length", ShortName = "ngram", SortOrder = 3)] 122Name = "AllLengths", ShortName = "all", SortOrder = 4)] 127ShortName = "skips", SortOrder = 3)] 132Name = "HashBits", ShortName = "bits", SortOrder = 2)] 138[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to rehash unigrams", ShortName = "rehash")] 143ShortName = "ord", SortOrder = 6)] 147ShortName = "ih")]
Text\NgramTransform.cs (9)
40[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum n-gram length", ShortName = "ngram")] 44"Whether to include all n-gram lengths up to " + nameof(NgramLength) + " or only " + nameof(NgramLength), Name = "AllLengths", ShortName = "all")] 49ShortName = "skips")] 52[Argument(ArgumentType.Multiple, HelpText = "Maximum number of n-grams to store in the dictionary", ShortName = "max")] 79[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 82[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum n-gram length", ShortName = "ngram")] 86"Whether to store all n-gram lengths up to ngramLength, or only ngramLength", Name = "AllLengths", ShortName = "all")] 91ShortName = "skips")] 94[Argument(ArgumentType.Multiple, HelpText = "Maximum number of n-grams to store in the dictionary", ShortName = "max")]
Text\SentimentAnalyzingTransform.cs (2)
25[Argument(ArgumentType.Required, HelpText = "Name of the source column.", ShortName = "col", Purpose = SpecialPurpose.ColumnName, SortOrder = 1)] 28[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the new column.", ShortName = "dst", SortOrder = 2)]
Text\StopWordsRemovingTransformer.cs (8)
73ShortName = "langscol")] 76[Argument(ArgumentType.AtMostOnce, HelpText = "Stopword Language (optional).", ShortName = "lang")] 100[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)] 105ShortName = "langscol", SortOrder = 1, 109[Argument(ArgumentType.AtMostOnce, HelpText = "Language-specific stop words list.", ShortName = "lang", SortOrder = 1)] 715[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "Data file containing the stopwords", ShortName = "data", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 721[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the text column containing the stopwords", ShortName = "stopwordsCol", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 727[Argument(ArgumentType.Multiple, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)]
Text\TextFeaturizingEstimator.cs (12)
128[Argument(ArgumentType.Required, HelpText = "New column definition (optional form: name:srcs).", Name = "Column", ShortName = "col", SortOrder = 1)] 131[Argument(ArgumentType.AtMostOnce, HelpText = "Dataset language or 'AutoDetect' to detect language per row.", ShortName = "lang", SortOrder = 3)] 134[Argument(ArgumentType.Multiple, Name = "StopWordsRemover", HelpText = "Stopwords remover.", ShortName = "remover", NullName = "<None>", SortOrder = 4)] 185[Argument(ArgumentType.AtMostOnce, HelpText = "Casing text using the rules of the invariant culture.", Name = "TextCase", ShortName = "case", SortOrder = 5)] 188[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to keep diacritical marks or remove them.", ShortName = "diac", SortOrder = 6)] 191[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to keep punctuation marks or remove them.", ShortName = "punc", SortOrder = 7)] 194[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to keep numbers or remove them.", ShortName = "num", SortOrder = 8)] 197[Argument(ArgumentType.AtMostOnce, HelpText = "Column containing the transformed text tokens.", ShortName = "tokens,showtext,showTransformedText", SortOrder = 9)] 200[Argument(ArgumentType.Multiple, HelpText = "A dictionary of allowed terms.", ShortName = "dict", NullName = "<None>", SortOrder = 10, Hide = true)] 204[Argument(ArgumentType.Multiple, Name = "WordFeatureExtractor", HelpText = "Ngram feature extractor to use for words (WordBag/WordHashBag).", ShortName = "wordExtractor", NullName = "<None>", SortOrder = 11)] 215[Argument(ArgumentType.AtMostOnce, HelpText = "Normalize vectors (rows) individually by rescaling them to unit norm.", Name = "VectorNormalizer", ShortName = "norm", SortOrder = 13)] 245[Argument(ArgumentType.Multiple, Name = "CharFeatureExtractor", HelpText = "Ngram feature extractor to use for characters (WordBag/WordHashBag).", ShortName = "charExtractor", NullName = "<None>", SortOrder = 12)]
Text\TextNormalizing.cs (5)
56[Argument(ArgumentType.Multiple, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)] 59[Argument(ArgumentType.AtMostOnce, HelpText = "Casing text using the rules of the invariant culture.", ShortName = "case", SortOrder = 1)] 63ShortName = "diac", SortOrder = 1)] 66[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to keep punctuation marks or remove them.", ShortName = "punc", SortOrder = 2)] 69[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to keep numbers or remove them.", ShortName = "num", SortOrder = 2)]
Text\TokenizingByCharacters.cs (2)
56[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 60ShortName = "mark", SortOrder = 2)]
Text\WordBagTransform.cs (17)
58[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length", ShortName = "ngram")] 63ShortName = "skips")] 68Name = "AllLengths", ShortName = "all")] 71[Argument(ArgumentType.Multiple, HelpText = "Maximum number of n-grams to store in the dictionary", ShortName = "max")] 101[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:srcs)", Name = "Column", ShortName = "col", SortOrder = 1)] 359[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length (stores all lengths up to the specified Ngram length)", ShortName = "ngram")] 364ShortName = "skips")] 369Name = "AllLengths", ShortName = "all")] 375[Argument(ArgumentType.Multiple, HelpText = "Maximum number of n-grams to store in the dictionary", ShortName = "max")] 409[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length", ShortName = "ngram")] 414ShortName = "skips")] 419Name = "AllLengths", ShortName = "all")] 422[Argument(ArgumentType.Multiple, HelpText = "Maximum number of n-grams to store in the dictionary", ShortName = "max")] 448[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 594[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "Data file containing the terms", ShortName = "data", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 600[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the text column containing the terms", ShortName = "termCol", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 607[Argument(ArgumentType.AtMostOnce, HelpText = "Drop unknown terms instead of mapping them to NA term.", ShortName = "dropna", SortOrder = 6)]
Text\WordEmbeddingsExtractor.cs (3)
61[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 0)] 64[Argument(ArgumentType.AtMostOnce, HelpText = "Pre-trained model used to create the vocabulary", ShortName = "model", SortOrder = 1)] 68ShortName = "dataFile", SortOrder = 2)]
Text\WordHashBagProducingTransform.cs (14)
78Name = "Column", ShortName = "col", SortOrder = 1)] 171[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length (stores all lengths up to the specified Ngram length)", ShortName = "ngram")] 176ShortName = "skips")] 181ShortName = "bits")] 187[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the position of each source column should be included in the hash (when there are multiple source columns).", ShortName = "ord")] 192ShortName = "ih")] 197Name = "AllLengths", ShortName = "all", SortOrder = 4)] 259[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length", ShortName = "ngram", SortOrder = 3)] 264ShortName = "skips", SortOrder = 4)] 269ShortName = "bits", SortOrder = 2)] 277ShortName = "ord")] 282ShortName = "ih")] 287Name = "AllLengths", ShortName = "all", SortOrder = 4)] 314[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:srcs)", Name = "Column", ShortName = "col", SortOrder = 1)]
Text\WordTokenizing.cs (4)
44ShortName = "sep")] 71ShortName = "sep")] 77ShortName = "sep")] 83[Argument(ArgumentType.Multiple, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)]
UngroupTransform.cs (1)
88[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to unroll, or 'pivot'", Name = "Column", ShortName = "col")]
Microsoft.ML.Vision (7)
DnnRetrainTransform.cs (7)
1127[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "The names of the model inputs", ShortName = "inputs", SortOrder = 1)] 1133[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "The name of the outputs", ShortName = "outputs", SortOrder = 2)] 1139[Argument(ArgumentType.AtMostOnce, HelpText = "Training labels.", ShortName = "label", SortOrder = 4)] 1145[Argument(ArgumentType.AtMostOnce, HelpText = "TensorFlow label node.", ShortName = "TFLabel", SortOrder = 5)] 1153[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the optimization operation in the TensorFlow graph.", ShortName = "OptimizationOp", SortOrder = 6)] 1159[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the operation in the TensorFlow graph to compute training loss (Optional)", ShortName = "LossOp", SortOrder = 7)] 1165[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the operation in the TensorFlow graph to compute performance metric during training (Optional)", ShortName = "MetricOp", SortOrder = 8)]
2 references to ShortName
Microsoft.ML.Core (2)
CommandLine\CmdParser.cs (2)
489if (attr.ShortName == null) 493nicks = attr.ShortName.Split(new char[] { ',', ' ' }, StringSplitOptions.RemoveEmptyEntries);