629 writes to SortOrder
Microsoft.ML.Core (1)
CommandLine\ArgumentAttribute.cs (1)
37SortOrder = 150;
Microsoft.ML.Data (134)
Commands\CrossValidationCommand.cs (9)
33[Argument(ArgumentType.Multiple, HelpText = "Scorer to use", NullName = "<Auto>", SortOrder = 101, SignatureType = typeof(SignatureDataScorer))] 36[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))] 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)]
Commands\DataCommand.cs (5)
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)] 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)]
Commands\EvaluateCommand.cs (9)
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)] 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)]
Commands\ScoreCommand.cs (1)
54Name = "CustomColumn", ShortName = "col", SortOrder = 10)]
Commands\TestCommand.cs (8)
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)] 47[Argument(ArgumentType.Multiple, HelpText = "Scorer to use", NullName = "<Auto>", SortOrder = 101, SignatureType = typeof(SignatureDataScorer))] 50[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))]
Commands\TrainCommand.cs (6)
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)]
Commands\TrainTestCommand.cs (9)
25[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The test data file", ShortName = "test", SortOrder = 1)] 31[Argument(ArgumentType.Multiple, HelpText = "Scorer to use", NullName = "<Auto>", SortOrder = 101, SignatureType = typeof(SignatureDataScorer))] 34[Argument(ArgumentType.Multiple, HelpText = "Evaluator to use", ShortName = "eval", NullName = "<Auto>", SortOrder = 102, SignatureType = typeof(SignatureMamlEvaluator))] 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)]
DataLoadSave\Binary\BinaryLoader.cs (1)
2105[DefaultArgument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "The data file", SortOrder = 0)]
DataLoadSave\Database\DatabaseLoader.cs (1)
352Name = "Column", ShortName = "col", SortOrder = 1)]
DataLoadSave\Text\TextLoader.cs (1)
486Name = "Column", ShortName = "col", SortOrder = 1)]
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)]
Model\Pfa\SavePfaCommand.cs (8)
30[Argument(ArgumentType.AtMostOnce, HelpText = "The path to write the output PFA too. Leave empty for stdout.", SortOrder = 1)] 33[Argument(ArgumentType.AtMostOnce, HelpText = "The 'name' property in the output PFA program. By default this will be the extension-less name ", NullName = "<Auto>", SortOrder = 3)] 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 (4)
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 (2)
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)]
Scorers\FeatureContributionCalculation.cs (4)
40[Argument(ArgumentType.AtMostOnce, HelpText = "Number of top contributions", SortOrder = 1)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "Number of bottom contributions", SortOrder = 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)]
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\ColumnConcatenatingTransformer.cs (2)
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 (5)
35[Argument(ArgumentType.Required, HelpText = "The predictor model to apply to data", SortOrder = 1)] 38[Argument(ArgumentType.AtMostOnce, HelpText = "Name of feature column", SortOrder = 2)] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Number of top contributions", SortOrder = 3)] 44[Argument(ArgumentType.AtMostOnce, HelpText = "Number of bottom contributions", SortOrder = 4)] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Whether or not output of Features contribution should be normalized", ShortName = "norm", SortOrder = 5)]
Transforms\GenerateNumberTransform.cs (1)
90Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\Hashing.cs (2)
40Name = "Column", ShortName = "col", SortOrder = 1)] 44ShortName = "bits", SortOrder = 2)]
Transforms\KeyToValue.cs (1)
60Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\KeyToVector.cs (1)
88Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\LabelIndicatorTransform.cs (1)
71[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\NAFilter.cs (1)
38[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Column", Name = "Column", ShortName = "col", SortOrder = 1)]
Transforms\NormalizeColumn.cs (6)
173[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 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)] 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\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 (11)
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, 120SortOrder = 105, Purpose = SpecialPurpose.ColumnName)] 124SortOrder = 104, Purpose = SpecialPurpose.ColumnName)] 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))]
Transforms\TransformInputBase.cs (1)
23[Argument(ArgumentType.Required, HelpText = "Input dataset", Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, SortOrder = 1)]
Transforms\TypeConverting.cs (2)
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)]
Transforms\ValueMapping.cs (2)
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)]
Transforms\ValueToKeyMappingTransformer.cs (9)
99[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum number of keys to keep per column when auto-training", ShortName = "max", SortOrder = 5)] 102[Argument(ArgumentType.AtMostOnce, HelpText = "Comma separated list of terms", Name = "Terms", SortOrder = 105, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 105[Argument(ArgumentType.AtMostOnce, HelpText = "List of terms", Name = "Term", SortOrder = 106, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 108[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "Data file containing the terms", ShortName = "data", SortOrder = 110, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 111[Argument(ArgumentType.Multiple, HelpText = "Data loader", NullName = "<Auto>", SortOrder = 111, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureDataLoader))] 115[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the text column containing the terms", ShortName = "termCol", SortOrder = 112, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 124"If by value items are sorted according to their default comparison, for example, text sorting will be case sensitive (for example, 'A' then 'Z' then 'a').", SortOrder = 113)] 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)]
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 (76)
CrossValidationMacro.cs (23)
28[Argument(ArgumentType.Required, HelpText = "The data to be used for training", SortOrder = 1)] 34[Argument(ArgumentType.AtMostOnce, HelpText = "The predictor model", SortOrder = 1)] 43[Argument(ArgumentType.Required, HelpText = "The data set", SortOrder = 1)] 48"It gets included in the Output.PredictorModel.", SortOrder = 2)] 53[Argument(ArgumentType.Required, HelpText = "The training subgraph", SortOrder = 3)] 58[Argument(ArgumentType.Required, HelpText = "The training subgraph inputs", SortOrder = 4)] 63[Argument(ArgumentType.Required, HelpText = "The training subgraph outputs", SortOrder = 5)] 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)] 77[Argument(ArgumentType.Required, HelpText = "Specifies the trainer kind, which determines the evaluator to be used.", SortOrder = 8)] 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)] 116[Argument(ArgumentType.Multiple, HelpText = "Overall metrics datasets", SortOrder = 1)] 119[Argument(ArgumentType.Multiple, HelpText = "Per instance metrics datasets", SortOrder = 2)] 122[Argument(ArgumentType.Multiple, HelpText = "Confusion matrix datasets", SortOrder = 3)] 125[Argument(ArgumentType.Multiple, HelpText = "Warning datasets", SortOrder = 4)] 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)] 140[Argument(ArgumentType.Required, HelpText = "Specifies the trainer kind, which determines the evaluator to be used.", SortOrder = 5)]
CVSplit.cs (3)
24[Argument(ArgumentType.Required, HelpText = "Input dataset", SortOrder = 1)] 27[Argument(ArgumentType.AtMostOnce, HelpText = "Number of folds to split into", SortOrder = 2)] 30[Argument(ArgumentType.AtMostOnce, ShortName = "strat", HelpText = "Stratification column", SortOrder = 3)]
DataViewReference.cs (1)
18[Argument(ArgumentType.Required, HelpText = "Pointer to IDataView in memory", SortOrder = 1)]
FeatureCombiner.cs (4)
25[Argument(ArgumentType.Multiple, HelpText = "Features", SortOrder = 2)] 207[Argument(ArgumentType.Required, HelpText = "The label column", SortOrder = 2)] 217[Argument(ArgumentType.AtMostOnce, HelpText = "Convert the key values to text", SortOrder = 3)] 223[Argument(ArgumentType.Required, HelpText = "The predicted label column", SortOrder = 2)]
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)]
MacroUtils.cs (2)
78[Argument(ArgumentType.Required, HelpText = "The models", SortOrder = 1)] 100[Argument(ArgumentType.Required, HelpText = "The data sets", SortOrder = 1)]
ModelOperations.cs (9)
22[Argument(ArgumentType.Multiple, HelpText = "Input models", SortOrder = 1)] 34[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Transform model", SortOrder = 1)] 37[Argument(ArgumentType.Required, HelpText = "Predictor model", SortOrder = 2)] 43[Argument(ArgumentType.Required, HelpText = "Transform model", SortOrder = 1)] 46[Argument(ArgumentType.Required, HelpText = "Predictor model", SortOrder = 2)] 58[Argument(ArgumentType.Multiple, HelpText = "Input models", SortOrder = 1)] 61[Argument(ArgumentType.AtMostOnce, HelpText = "Use probabilities from learners instead of raw values.", SortOrder = 2)] 67[Argument(ArgumentType.Multiple, HelpText = "Input models", SortOrder = 1)] 73[Argument(ArgumentType.Required, HelpText = "Transform model", SortOrder = 2)]
OneVersusAllMacro.cs (4)
27[Argument(ArgumentType.Required, HelpText = "The predictor model for the subgraph exemplar.", SortOrder = 1)] 35[Argument(ArgumentType.Required, HelpText = "The subgraph for the binary trainer used to construct the OVA learner. This should be a TrainBinary node.", SortOrder = 1)] 38[Argument(ArgumentType.Required, HelpText = "The training subgraph output.", SortOrder = 2)] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Use probabilities in OVA combiner", SortOrder = 3)]
ScoreColumnSelector.cs (2)
19[Argument(ArgumentType.Multiple, HelpText = "Extra columns to write", SortOrder = 2)] 60[Argument(ArgumentType.Required, HelpText = "The predictor model used in scoring", SortOrder = 2)]
ScoreModel.cs (6)
27[Argument(ArgumentType.Required, HelpText = "The dataset to be scored", SortOrder = 1)] 30[Argument(ArgumentType.Required, HelpText = "The predictor model to apply to data", SortOrder = 2)] 33[Argument(ArgumentType.AtMostOnce, HelpText = "Suffix to append to the score columns", SortOrder = 3)] 39[Argument(ArgumentType.Required, HelpText = "The dataset to be scored", SortOrder = 1)] 42[Argument(ArgumentType.Required, HelpText = "The transform model to apply to data", SortOrder = 2)] 57[Argument(ArgumentType.Required, HelpText = "The predictor model to turn into a transform", SortOrder = 1)]
TrainTestMacro.cs (15)
22[Argument(ArgumentType.Required, HelpText = "The data to be used for training", SortOrder = 1)] 28[Argument(ArgumentType.AtMostOnce, HelpText = "The predictor model", SortOrder = 1)] 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)] 43[Argument(ArgumentType.AtMostOnce, HelpText = "The aggregated transform model from the pipeline before this command, to apply to the test data, and also include in the final model, together with the predictor model.", SortOrder = 3)] 46[Argument(ArgumentType.Required, HelpText = "The training subgraph", SortOrder = 4)] 49[Argument(ArgumentType.Required, HelpText = "The training subgraph inputs", SortOrder = 5)] 52[Argument(ArgumentType.Required, HelpText = "The training subgraph outputs", SortOrder = 6)] 55[Argument(ArgumentType.AtMostOnce, HelpText = "Specifies the trainer kind, which determines the evaluator to be used.", SortOrder = 7)] 58[Argument(ArgumentType.AtMostOnce, HelpText = "Identifies which pipeline was run for this train test.", SortOrder = 8)] 61[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates whether to include and output training dataset metrics.", SortOrder = 9)] 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 (3)
20[Argument(ArgumentType.Required, HelpText = "Input dataset", SortOrder = 1)] 23[Argument(ArgumentType.AtMostOnce, HelpText = "Fraction of training data", SortOrder = 2)] 26[Argument(ArgumentType.AtMostOnce, ShortName = "strat", HelpText = "Stratification column", SortOrder = 3)]
Microsoft.ML.FastTree (23)
FastTreeArguments.cs (4)
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)] 754[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The learning rate", ShortName = "lr", SortOrder = 4)]
GamModelParameters.cs (1)
557[Argument(ArgumentType.AtMostOnce, HelpText = "Whether to open the GAM visualization page URL", ShortName = "o", SortOrder = 3)]
GamTrainer.cs (3)
56[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Total number of iterations over all features", ShortName = "iter", SortOrder = 1)] 70[Argument(ArgumentType.LastOccurrenceWins, HelpText = "The learning rate", ShortName = "lr", SortOrder = 4)] 108[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Minimum number of training instances required to form a partition", ShortName = "mi", SortOrder = 3)]
SumupPerformanceCommand.cs (8)
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)] 65HelpText = "Desired degree of parallelism in the data pipeline", ShortName = "n", SortOrder = 6)]
TreeEnsembleFeaturizer.cs (7)
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)] 571[Argument(ArgumentType.Required, HelpText = "Trainer to use", SortOrder = 10, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)]
Microsoft.ML.ImageAnalytics (5)
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 (1)
59[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
ImagePixelExtractor.cs (1)
92[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
ImageResizer.cs (1)
72[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
VectorToImageTransform.cs (1)
106[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
Microsoft.ML.KMeansClustering (2)
KMeansPlusPlusTrainer.cs (2)
110[Argument(ArgumentType.AtMostOnce, HelpText = "The number of clusters", SortOrder = 50, Name = "K")] 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 (5)
LightGbmTrainerBase.cs (5)
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>")] 136SortOrder = 3)]
Microsoft.ML.Mkl.Components (5)
OlsLinearRegression.cs (1)
82[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularization weight", ShortName = "l2", SortOrder = 50)]
SymSgdClassificationTrainer.cs (3)
95[Argument(ArgumentType.AtMostOnce, HelpText = "Number of passes over the data.", ShortName = "iter", SortOrder = 50)] 110[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate", ShortName = "lr", NullName = "<Auto>", SortOrder = 51)] 118[Argument(ArgumentType.AtMostOnce, HelpText = "L2 regularization", ShortName = "l2", SortOrder = 52)]
VectorWhitening.cs (1)
54[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
Microsoft.ML.OnnxConverter (12)
SaveOnnxCommand.cs (12)
36[Argument(ArgumentType.Required, HelpText = "The path to write the output ONNX to.", SortOrder = 1)] 39[Argument(ArgumentType.AtMostOnce, HelpText = "The path to write the output JSON to.", SortOrder = 2)] 42[Argument(ArgumentType.AtMostOnce, HelpText = "The 'name' property in the output ONNX. By default this will be the ONNX extension-less name.", NullName = "<Auto>", SortOrder = 3)] 45[Argument(ArgumentType.AtMostOnce, HelpText = "The 'domain' property in the output ONNX.", NullName = "<Auto>", SortOrder = 4)] 48[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of input column names to drop", ShortName = "idrop", SortOrder = 5)] 51[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of input column names to drop", Name = nameof(InputsToDrop), SortOrder = 6)] 54[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, HelpText = "Comma delimited list of output column names to drop", ShortName = "odrop", SortOrder = 7)] 57[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Array of output column names to drop", Name = nameof(OutputsToDrop), SortOrder = 8)] 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)] 67[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Model that needs to be converted to ONNX format.", SortOrder = 10)] 74[Argument(ArgumentType.AtMostOnce, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly, HelpText = "Predictor model that needs to be converted to ONNX format.", SortOrder = 12)] 77[Argument(ArgumentType.AtMostOnce, HelpText = "The targeted ONNX version. It can be either \"Stable\" or \"Experimental\". If \"Experimental\" is used, produced model can contain components that is not officially supported in ONNX standard.", SortOrder = 11)]
Microsoft.ML.OnnxTransformer (9)
OnnxTransform.cs (9)
73[Argument(ArgumentType.Required, HelpText = "Path to the onnx model file.", ShortName = "model", SortOrder = 0)] 76[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Name of the input column.", SortOrder = 1)] 79[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Name of the output column.", SortOrder = 2)] 82[Argument(ArgumentType.AtMostOnce, HelpText = "GPU device id to run on (e.g. 0,1,..). Null for CPU. Requires CUDA 9.1.", SortOrder = 3)] 85[Argument(ArgumentType.AtMostOnce, HelpText = "If true, resumes execution on CPU upon GPU error. If false, will raise the GPU exception.", SortOrder = 4)] 88[Argument(ArgumentType.Multiple, HelpText = "Shapes used to overwrite shapes loaded from ONNX file.", SortOrder = 5)] 91[Argument(ArgumentType.AtMostOnce, HelpText = "Protobuf CodedInputStream recursion limit.", SortOrder = 6)] 94[Argument(ArgumentType.AtMostOnce, HelpText = "Controls the number of threads used to parallelize the execution of the graph (across nodes).", SortOrder = 7)] 97[Argument(ArgumentType.AtMostOnce, HelpText = "Controls the number of threads to use to run the model.", SortOrder = 8)]
Microsoft.ML.Parquet (1)
PartitionedPathParser.cs (1)
81ShortName = "col", SortOrder = 1)]
Microsoft.ML.PCA (3)
PcaTrainer.cs (2)
96[Argument(ArgumentType.AtMostOnce, HelpText = "The number of components in the PCA", ShortName = "k", SortOrder = 50)] 101[Argument(ArgumentType.AtMostOnce, HelpText = "Oversampling parameter for randomized PCA training", SortOrder = 50)]
PcaTransformer.cs (1)
40[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
Microsoft.ML.StandardTrainers (50)
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 (6)
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)] 132HelpText = "Number of iterations", ShortName = "iter,NumIterations", SortOrder = 50)]
Standard\LogisticRegression\LbfgsPredictorBase.cs (6)
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)] 112[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Init weights diameter", ShortName = "initwts, InitWtsDiameter", SortOrder = 140)] 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\Online\AveragedLinear.cs (3)
27[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate", ShortName = "lr", SortOrder = 50)] 40[Argument(ArgumentType.AtMostOnce, HelpText = "Decrease learning rate", ShortName = "decreaselr", SortOrder = 50)] 69[Argument(ArgumentType.AtMostOnce, HelpText = "L2 Regularization Weight", ShortName = "reg,L2RegularizerWeight", SortOrder = 50)]
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 (2)
27[Argument(ArgumentType.AtMostOnce, HelpText = "Number of iterations", ShortName = "iter,numIterations", SortOrder = 50)] 47[Argument(ArgumentType.AtMostOnce, HelpText = "Init weights diameter", ShortName = "initwts,initWtsDiameter", SortOrder = 140)]
Standard\SdcaBinary.cs (9)
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)] 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)] 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.TensorFlow (6)
TensorflowTransform.cs (6)
937[Argument(ArgumentType.Required, HelpText = "TensorFlow model used by the transform. Please see https://www.tensorflow.org/mobile/prepare_models for more details.", SortOrder = 0)] 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)] 955[Argument(ArgumentType.AtMostOnce, HelpText = "Number of samples to use for mini-batch training.", SortOrder = 9)] 965[Argument(ArgumentType.AtMostOnce, HelpText = "Add a batch dimension to the input e.g. input = [224, 224, 3] => [-1, 224, 224, 3].", SortOrder = 16)] 974[Argument(ArgumentType.AtMostOnce, HelpText = "If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unknown length when this is false.", SortOrder = 17)]
Microsoft.ML.TimeSeries (116)
AdaptiveSingularSpectrumSequenceModeler.cs (2)
38[Argument(ArgumentType.AtMostOnce, HelpText = "Time span of growth ratio. Must be strictly positive.", SortOrder = 1)] 41[Argument(ArgumentType.AtMostOnce, HelpText = "Growth. Must be non-negative.", SortOrder = 2)]
ExponentialAverageTransform.cs (3)
34SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 38SortOrder = 2)] 42ShortName = "d", SortOrder = 4)]
IidChangePointDetector.cs (6)
41SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 45SortOrder = 2)] 49SortOrder = 102)] 53ShortName = "cnf", SortOrder = 3)] 56[Argument(ArgumentType.AtMostOnce, HelpText = "The martingale used for scoring.", ShortName = "mart", SortOrder = 103)] 60ShortName = "eps", SortOrder = 104)]
IidSpikeDetector.cs (5)
40SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 44SortOrder = 2)] 48SortOrder = 101)] 52SortOrder = 102)] 56ShortName = "cnf", SortOrder = 3)]
MovingAverageTransform.cs (5)
33SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 37SortOrder = 2)] 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)
34SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 38SortOrder = 2)] 42SortOrder = 3)] 47SortOrder = 4)]
PValueTransform.cs (6)
34SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 38SortOrder = 2)] 42SortOrder = 3)] 46SortOrder = 4)] 50SortOrder = 5)] 54ShortName = "initwnd", SortOrder = 6)]
SequentialAnomalyDetectionTransformBase.cs (9)
79SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 83SortOrder = 2)] 87SortOrder = 3)] 91SortOrder = 4)] 95ShortName = "initwnd", SortOrder = 5)] 99ShortName = "martingale", SortOrder = 6)] 103ShortName = "alert", SortOrder = 7)] 107ShortName = "eps", SortOrder = 8)] 111ShortName = "thr", SortOrder = 9)]
SequentialForecastingTransformBase.cs (6)
22SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 26SortOrder = 2)] 30SortOrder = 2)] 34SortOrder = 2)] 38SortOrder = 3)] 42"is set to 0, which means there is no initial window considered.", ShortName = "initwnd", SortOrder = 5)]
SlidingWindowTransformBase.cs (5)
42SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 46SortOrder = 2)] 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)] 55[Argument(ArgumentType.AtMostOnce, HelpText = "Define how to populate the first rows of the produced series", SortOrder = 5)]
SRCNNAnomalyDetector.cs (8)
40SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 44SortOrder = 2)] 48SortOrder = 101)] 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 (9)
18SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 22SortOrder = 2)] 26SortOrder = 3)] 30SortOrder = 4)] 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 (9)
41SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 45SortOrder = 2)] 49SortOrder = 102)] 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 (18)
38[Argument(ArgumentType.Required, HelpText = "The name of the source column.", ShortName = "src", SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 41[Argument(ArgumentType.Required, HelpText = "The name of the new column.", SortOrder = 2)] 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)] 56[Argument(ArgumentType.Required, HelpText = "The length of the window on the series for building the trajectory matrix (parameter L).", SortOrder = 2)] 59[Argument(ArgumentType.AtMostOnce, HelpText = "The rank selection method.", SortOrder = 3)] 63"If set to null, the rank is automatically determined based on prediction error minimization.", SortOrder = 3)] 66[Argument(ArgumentType.AtMostOnce, HelpText = "The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.", SortOrder = 3)] 69[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)] 72[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)] 75[Argument(ArgumentType.AtMostOnce, HelpText = "The maximum growth on the exponential trend.", SortOrder = 3)] 78[Argument(ArgumentType.Required, HelpText = "The length of series that is kept in buffer for modeling (parameter N).", SortOrder = 2)] 81[Argument(ArgumentType.Required, HelpText = "The length of series from the beginning used for training.", SortOrder = 2)] 84[Argument(ArgumentType.Required, HelpText = "The number of values to forecast.", SortOrder = 2)] 87[Argument(ArgumentType.AtMostOnce, HelpText = "The confidence level in [0, 1) for forecasting.", SortOrder = 2)] 90[Argument(ArgumentType.AtMostOnce, HelpText = "Set this to true horizon will change at prediction time.", SortOrder = 2)]
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 (8)
40SortOrder = 1, Purpose = SpecialPurpose.ColumnName)] 44SortOrder = 2)] 48SortOrder = 101)] 52SortOrder = 102)] 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 (109)
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\CountTableTransformer.cs (1)
356[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", ShortName = "col", SortOrder = 1)]
Dracula\CountTargetEncodingTransformer.cs (2)
57ShortName = "col", SortOrder = 1)] 81[Argument(ArgumentType.AtMostOnce, HelpText = "Whether the values need to be combined for a single hash", SortOrder = 3)]
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.")]
GcnTransform.cs (6)
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)] 51[Argument(ArgumentType.AtMostOnce, HelpText = "Subtract mean from each value before normalizing", SortOrder = 2)] 57[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 60[Argument(ArgumentType.AtMostOnce, HelpText = "Subtract mean from each value before normalizing", SortOrder = 1)] 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 (2)
52SortOrder = 1)] 59ShortName = "bits", SortOrder = 2)]
KeyToVectorMapping.cs (1)
38Name = "Column", ShortName = "col", SortOrder = 1)]
LearnerFeatureSelection.cs (6)
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)]
LoadTransform.cs (3)
32SortOrder = 1, IsInputFileName = true)] 36Name = "Tag", SortOrder = 2)] 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 (2)
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)]
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 (1)
118[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:rep:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
MutualInformationFeatureSelection.cs (3)
91[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "Columns to use for feature selection", Name = "Column", ShortName = "col", SortOrder = 1)] 95SortOrder = 4, Purpose = SpecialPurpose.ColumnName)] 99SortOrder = 1)]
OneHotEncoding.cs (2)
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 (4)
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)] 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 (1)
38[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
SvmLight\SvmLightSaver.cs (4)
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 (4)
56[Argument(ArgumentType.Multiple | ArgumentType.Required, HelpText = "New column definition(s) (optional form: name:srcs)", Name = "Column", ShortName = "col", SortOrder = 49)] 59[Argument(ArgumentType.AtMostOnce, HelpText = "The number of topics", SortOrder = 50)] 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)]
Text\NgramHashingTransformer.cs (6)
114SortOrder = 1)] 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)] 143ShortName = "ord", SortOrder = 6)]
Text\NgramTransform.cs (1)
79[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)]
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 (7)
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)] 718[Argument(ArgumentType.Multiple, HelpText = "Data loader", NullName = "<Auto>", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureDataLoader))] 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 (9)
101[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:srcs)", Name = "Column", ShortName = "col", SortOrder = 1)] 448[Argument(ArgumentType.Multiple, HelpText = "New column definition(s) (optional form: name:src)", Name = "Column", ShortName = "col", SortOrder = 1)] 588[Argument(ArgumentType.AtMostOnce, HelpText = "Comma separated list of terms", Name = "Terms", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 591[Argument(ArgumentType.AtMostOnce, HelpText = "List of terms", Name = "Term", SortOrder = 1, Visibility = ArgumentAttribute.VisibilityType.EntryPointsOnly)] 594[Argument(ArgumentType.AtMostOnce, IsInputFileName = true, HelpText = "Data file containing the terms", ShortName = "data", SortOrder = 2, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 597[Argument(ArgumentType.Multiple, HelpText = "Data loader", NullName = "<Auto>", SortOrder = 3, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly, SignatureType = typeof(SignatureDataLoader))] 600[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the text column containing the terms", ShortName = "termCol", SortOrder = 4, Visibility = ArgumentAttribute.VisibilityType.CmdLineOnly)] 604"If by value, items are sorted according to their default comparison, for example, text sorting will be case sensitive (for example, 'A' then 'Z' then 'a').", SortOrder = 5)] 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 (7)
78Name = "Column", ShortName = "col", SortOrder = 1)] 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)] 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 (1)
83[Argument(ArgumentType.Multiple, HelpText = "New column definition(s)", Name = "Column", ShortName = "col", SortOrder = 1)]
Microsoft.ML.Vision (33)
DnnRetrainTransform.cs (15)
1121[Argument(ArgumentType.Required, HelpText = "TensorFlow model used by the transform. Please see https://www.tensorflow.org/mobile/prepare_models for more details.", SortOrder = 0)] 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)] 1171[Argument(ArgumentType.AtMostOnce, HelpText = "Number of samples to use for mini-batch training.", SortOrder = 9)] 1177[Argument(ArgumentType.AtMostOnce, HelpText = "Number of training iterations.", SortOrder = 10)] 1183[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the operation in the TensorFlow graph which sets optimizer learning rate (Optional).", SortOrder = 11)] 1189[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate to use during optimization.", SortOrder = 12)] 1198[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the input in TensorFlow graph that specify the location for saving/restoring models from disk.", SortOrder = 13)] 1207[Argument(ArgumentType.AtMostOnce, HelpText = "Name of the input in TensorFlow graph that specify the location for saving/restoring models from disk.", SortOrder = 14)] 1217[Argument(ArgumentType.AtMostOnce, HelpText = "Add a batch dimension to the input e.g. input = [224, 224, 3] => [-1, 224, 224, 3].", SortOrder = 16)]
ImageClassificationTrainer.cs (18)
351[Argument(ArgumentType.AtMostOnce, HelpText = "Number of samples to use for mini-batch training.", SortOrder = 9)] 357[Argument(ArgumentType.AtMostOnce, HelpText = "Number of training iterations.", SortOrder = 10)] 363[Argument(ArgumentType.AtMostOnce, HelpText = "Learning rate to use during optimization.", SortOrder = 12)] 369[Argument(ArgumentType.AtMostOnce, HelpText = "Early stopping technique parameters to be used to terminate training when training metric stops improving.", SortOrder = 15)] 375[Argument(ArgumentType.AtMostOnce, HelpText = "Model architecture to be used in transfer learning for image classification.", SortOrder = 15)] 381[Argument(ArgumentType.AtMostOnce, HelpText = "Softmax tensor of the last layer in transfer learning.", SortOrder = 15)] 387[Argument(ArgumentType.AtMostOnce, HelpText = "Argmax tensor of the last layer in transfer learning.", SortOrder = 15)] 393[Argument(ArgumentType.AtMostOnce, HelpText = "Final model and checkpoint files/folder prefix for storing graph files.", SortOrder = 15)] 399[Argument(ArgumentType.AtMostOnce, HelpText = "Callback to report metrics during training and validation phase.", SortOrder = 15)] 405[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates the path where the models get downloaded to and cache files saved, default is a new temporary directory.", SortOrder = 15)] 411[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates to evaluate the model on train set after every epoch.", SortOrder = 15)] 417[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates to not re-compute trained cached bottleneck values if already available in the bin folder.", SortOrder = 15)] 423[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates to not re-compute validataionset cached bottleneck validationset values if already available in the bin folder.", SortOrder = 15)] 429[Argument(ArgumentType.AtMostOnce, HelpText = "Validation set.", SortOrder = 15)] 437[Argument(ArgumentType.AtMostOnce, HelpText = "Validation fraction.", SortOrder = 15)] 443[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates the file name to store trainset bottleneck values for caching.", SortOrder = 15)] 449[Argument(ArgumentType.AtMostOnce, HelpText = "Indicates the file name to store validationset bottleneck values for caching.", SortOrder = 15)] 455[Argument(ArgumentType.AtMostOnce, HelpText = "A class that performs learning rate scheduling.", SortOrder = 15)]
3 references to SortOrder
Microsoft.ML.Core (1)
CommandLine\CmdParser.cs (1)
1434SortOrder = attr.SortOrder;
Microsoft.ML.EntryPoints (2)
JsonUtils\JsonManifestUtils.cs (2)
180jo[FieldNames.SortOrder] = inputAttr.SortOrder; 273inputs.Add(new KeyValuePair<Double, JObject>(inputAttr.SortOrder, jo));