629 writes to SortOrder
Microsoft.ML.Core (1)
CommandLine\ArgumentAttribute.cs (1)
37
SortOrder
= 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)]
61
Name = "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)]
136
Name = "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)]
189
Name = "CustomColumn", ShortName = "col",
SortOrder
= 10)]
Commands\ScoreCommand.cs (1)
54
Name = "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)]
44
Name = "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)]
59
Name = "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)]
56
Name = "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)
352
Name = "Column", ShortName = "col",
SortOrder
= 1)]
DataLoadSave\Text\TextLoader.cs (1)
486
Name = "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)
121
Name = "Column", ShortName = "col",
SortOrder
= 1)]
129
Name = "Column", ShortName = "col",
SortOrder
= 1)]
Transforms\ColumnCopying.cs (1)
142
Name = "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)
90
Name = "Column", ShortName = "col",
SortOrder
= 1)]
Transforms\Hashing.cs (2)
40
Name = "Column", ShortName = "col",
SortOrder
= 1)]
44
ShortName = "bits",
SortOrder
= 2)]
Transforms\KeyToValue.cs (1)
60
Name = "Column", ShortName = "col",
SortOrder
= 1)]
Transforms\KeyToVector.cs (1)
88
Name = "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)
44
Name = "Column", ShortName = "col",
SortOrder
= 1)]
Transforms\TrainAndScoreTransformer.cs (11)
28
ShortName = "feat",
SortOrder
= 1,
32
[Argument(ArgumentType.AtMostOnce, HelpText = "Group column name", ShortName = "group",
SortOrder
= 100,
38
Name = "CustomColumn", ShortName = "col",
SortOrder
= 101, Purpose = SpecialPurpose.ColumnSelector)]
45
ShortName = "in",
SortOrder
= 2)]
112
ShortName = "feat",
SortOrder
= 102, Purpose = SpecialPurpose.ColumnName)]
115
[Argument(ArgumentType.LastOccurrenceWins, HelpText = "Column to use for labels", ShortName = "lab",
SortOrder
= 103,
120
SortOrder
= 105, Purpose = SpecialPurpose.ColumnName)]
124
SortOrder
= 104, Purpose = SpecialPurpose.ColumnName)]
127
[Argument(ArgumentType.AtMostOnce, HelpText = "Name column name", ShortName = "name",
SortOrder
= 106,
133
Name = "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)
21
ShortName = "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)]
49
ShortName = "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)]
65
HelpText = "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))]
543
ShortName = "in",
SortOrder
= 2)]
547
ShortName = "ex",
SortOrder
= 101)]
551
ShortName = "lps",
SortOrder
= 102)]
564
ShortName = "ex",
SortOrder
= 101)]
568
ShortName = "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")]
95
SortOrder
= 2, ShortName = "lr", NullName = "<Auto>")]
104
SortOrder
= 2, ShortName = "nl", NullName = "<Auto>")]
113
SortOrder
= 2, ShortName = "mil", NullName = "<Auto>")]
136
SortOrder
= 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)
81
ShortName = "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)]
155
ShortName = "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)]
132
HelpText = "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)]
64
ShortName = "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)]
174
NullName = "<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)
34
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
38
SortOrder
= 2)]
42
ShortName = "d",
SortOrder
= 4)]
IidChangePointDetector.cs (6)
41
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
45
SortOrder
= 2)]
49
SortOrder
= 102)]
53
ShortName = "cnf",
SortOrder
= 3)]
56
[Argument(ArgumentType.AtMostOnce, HelpText = "The martingale used for scoring.", ShortName = "mart",
SortOrder
= 103)]
60
ShortName = "eps",
SortOrder
= 104)]
IidSpikeDetector.cs (5)
40
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
44
SortOrder
= 2)]
48
SortOrder
= 101)]
52
SortOrder
= 102)]
56
ShortName = "cnf",
SortOrder
= 3)]
MovingAverageTransform.cs (5)
33
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
37
SortOrder
= 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)]
48
ShortName = "w",
SortOrder
= 5)]
PercentileThresholdTransform.cs (4)
34
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
38
SortOrder
= 2)]
42
SortOrder
= 3)]
47
SortOrder
= 4)]
PValueTransform.cs (6)
34
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
38
SortOrder
= 2)]
42
SortOrder
= 3)]
46
SortOrder
= 4)]
50
SortOrder
= 5)]
54
ShortName = "initwnd",
SortOrder
= 6)]
SequentialAnomalyDetectionTransformBase.cs (9)
79
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
83
SortOrder
= 2)]
87
SortOrder
= 3)]
91
SortOrder
= 4)]
95
ShortName = "initwnd",
SortOrder
= 5)]
99
ShortName = "martingale",
SortOrder
= 6)]
103
ShortName = "alert",
SortOrder
= 7)]
107
ShortName = "eps",
SortOrder
= 8)]
111
ShortName = "thr",
SortOrder
= 9)]
SequentialForecastingTransformBase.cs (6)
22
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
26
SortOrder
= 2)]
30
SortOrder
= 2)]
34
SortOrder
= 2)]
38
SortOrder
= 3)]
42
"is set to 0, which means there is no initial window considered.", ShortName = "initwnd",
SortOrder
= 5)]
SlidingWindowTransformBase.cs (5)
42
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
46
SortOrder
= 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)
40
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
44
SortOrder
= 2)]
48
SortOrder
= 101)]
52
ShortName = "backwnd",
SortOrder
= 102)]
56
ShortName = "aheadwnd",
SortOrder
= 103)]
60
ShortName = "avgwnd",
SortOrder
= 104)]
64
ShortName = "jdgwnd",
SortOrder
= 105)]
68
ShortName = "thre",
SortOrder
= 106)]
SrCnnEntireAnomalyDetector.cs (6)
60
SortOrder
= 3, ShortName = "thr")]
64
SortOrder
= 4, ShortName = "bsz")]
68
SortOrder
= 4, ShortName = "sen")]
72
SortOrder
= 5, ShortName = "dtmd")]
76
SortOrder
= 5, ShortName = "prd")]
80
SortOrder
= 6, ShortName = "dsmd")]
SrCnnTransformBase.cs (9)
18
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
22
SortOrder
= 2)]
26
SortOrder
= 3)]
30
SortOrder
= 4)]
34
ShortName = "backwnd",
SortOrder
= 5)]
38
ShortName = "aheadwnd",
SortOrder
= 6)]
42
ShortName = "avgwnd",
SortOrder
= 7)]
46
ShortName = "jdgwnd",
SortOrder
= 8)]
50
ShortName = "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)
41
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
45
SortOrder
= 2)]
49
SortOrder
= 102)]
53
ShortName = "twnd",
SortOrder
= 3)]
57
ShortName = "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)]
70
ShortName = "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)
40
SortOrder
= 1, Purpose = SpecialPurpose.ColumnName)]
44
SortOrder
= 2)]
48
SortOrder
= 101)]
52
SortOrder
= 102)]
56
ShortName = "twnd",
SortOrder
= 3)]
60
ShortName = "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)
57
ShortName = "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)
52
SortOrder
= 1)]
59
ShortName = "bits",
SortOrder
= 2)]
KeyToVectorMapping.cs (1)
38
Name = "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)
32
SortOrder
= 1, IsInputFileName = true)]
36
Name = "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)]
95
SortOrder
= 4, Purpose = SpecialPurpose.ColumnName)]
99
SortOrder
= 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)]
78
ShortName = "kind",
SortOrder
= 102)]
OneHotHashEncoding.cs (4)
44
ShortName = "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)]
95
ShortName = "bits",
SortOrder
= 2)]
110
ShortName = "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)
114
SortOrder
= 1)]
117
[Argument(ArgumentType.AtMostOnce, HelpText = "Maximum n-gram length", ShortName = "ngram",
SortOrder
= 3)]
122
Name = "AllLengths", ShortName = "all",
SortOrder
= 4)]
127
ShortName = "skips",
SortOrder
= 3)]
132
Name = "HashBits", ShortName = "bits",
SortOrder
= 2)]
143
ShortName = "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)]
105
ShortName = "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)]
63
ShortName = "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)]
60
ShortName = "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)]
68
ShortName = "dataFile",
SortOrder
= 2)]
Text\WordHashBagProducingTransform.cs (7)
78
Name = "Column", ShortName = "col",
SortOrder
= 1)]
197
Name = "AllLengths", ShortName = "all",
SortOrder
= 4)]
259
[Argument(ArgumentType.AtMostOnce, HelpText = "Ngram length", ShortName = "ngram",
SortOrder
= 3)]
264
ShortName = "skips",
SortOrder
= 4)]
269
ShortName = "bits",
SortOrder
= 2)]
287
Name = "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)
1434
SortOrder = attr.
SortOrder
;
Microsoft.ML.EntryPoints (2)
JsonUtils\JsonManifestUtils.cs (2)
180
jo[FieldNames.SortOrder] = inputAttr.
SortOrder
;
273
inputs.Add(new KeyValuePair<Double, JObject>(inputAttr.
SortOrder
, jo));