Public/New-AmoebaMLPipelineTransform.ps1
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function New-AmoebaMLPipelineTransform { [CmdletBinding()] param( [ValidateSet( "ApproximateBootstrapSampler", "BinaryPredictionScoreColumnsRenamer", "NormalizeTransformBinColumn", "BinNormalizer", "CategoricalTransformOutputKind", "CategoricalHashTransformColumn", "CategoricalHashOneHotVectorizer", "TermTransformSortOrder", "CategoricalTransformColumn", "CategoricalOneHotVectorizer", "CharTokenizeTransformColumn", "CharacterTokenizer", "ConcatTransformColumn", "ColumnConcatenator", "CopyColumnsTransformColumn", "ColumnCopier", "ColumnDropper", "ColumnSelector", "DataKind", "ConvertTransformColumn", "ColumnTypeConverter", "CombinerByContiguousGroupId", "NormalizeTransformAffineColumn", "ConditionalNormalizer", "CacheCachingType", "DataCache", "DatasetScorer", "DatasetTransformScorer", "TermTransformColumn", "Dictionarizer", "FeatureCombiner", "FeatureSelectorByCount", "FeatureSelectorByMutualInformation", "LpNormNormalizerTransformGcnColumn", "GlobalContrastNormalizer", "HashJoinTransformColumn", "HashConverter", "KeyToValueTransformColumn", "KeyToTextConverter", "LabelColumnKeyBooleanConverter", "LabelIndicatorTransformColumn", "LabelIndicator", "LabelToFloatConverter", "NormalizeTransformLogNormalColumn", "LogMeanVarianceNormalizer", "LpNormNormalizerTransformNormalizerKind", "LpNormNormalizerTransformColumn", "LpNormalizer", "ManyHeterogeneousModelCombiner", "MeanVarianceNormalizer", "MinMaxNormalizer", "NAHandleTransformReplacementKind", "NAHandleTransformColumn", "MissingValueHandler", "NAIndicatorTransformColumn", "MissingValueIndicator", "NADropTransformColumn", "MissingValuesDropper", "MissingValuesRowDropper", "NAReplaceTransformReplacementKind", "NAReplaceTransformColumn", "MissingValueSubstitutor", "ModelCombiner", "NgramTransformWeightingCriteria", "NgramTransformColumn", "NGramTranslator", "NoOperation", "OptionalColumnCreator", "PredictedLabelColumnOriginalValueConverter", "GenerateNumberTransformColumn", "RandomNumberGenerator", "RowRangeFilter", "RowSkipAndTakeFilter", "RowSkipFilter", "RowTakeFilter", "ScoreColumnSelector", "Scorer", "UngroupTransformUngroupMode", "Segregator", "SentimentAnalyzer", "SupervisedBinNormalizer", "TextTransformLanguage", "TextNormalizerTransformCaseNormalizationMode", "TextTransformTextNormKind", "TextTransformColumn", "TermLoaderArguments", "TextFeaturizer", "TextToKeyConverter", "TrainTestDatasetSplitter", "TreeLeafFeaturizer", "TwoHeterogeneousModelCombiner", "DelimitedTokenizeTransformColumn", "WordTokenizer" )][System.String]$Type, [System.String]$outputColumn, [System.String[]]$inputColumns, [System.Tuple[String, String][]]$inputOutputColumns ) switch ($Type) { "ApproximateBootstrapSampler" { # Void .ctor() return [Microsoft.ML.Transforms.ApproximateBootstrapSampler]::new() } "BinaryPredictionScoreColumnsRenamer" { # Void .ctor() return [Microsoft.ML.Transforms.BinaryPredictionScoreColumnsRenamer]::new() } "NormalizeTransformBinColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NormalizeTransformBinColumn]::new() } "BinNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.BinNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.BinNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.BinNormalizer]::new() } "CategoricalHashTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.CategoricalHashTransformColumn]::new() } "CategoricalHashOneHotVectorizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.CategoricalHashOneHotVectorizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.CategoricalHashOneHotVectorizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.CategoricalHashOneHotVectorizer]::new() } "CategoricalTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.CategoricalTransformColumn]::new() } "CategoricalOneHotVectorizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.CategoricalOneHotVectorizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.CategoricalOneHotVectorizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.CategoricalOneHotVectorizer]::new() } "CharTokenizeTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.CharTokenizeTransformColumn]::new() } "CharacterTokenizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.CharacterTokenizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.CharacterTokenizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.CharacterTokenizer]::new() } "ConcatTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.ConcatTransformColumn]::new() } "ColumnConcatenator" { # Void .ctor() # Void .ctor(System.String, System.String[]) if (($outputColumn) -and ($inputColumns)) { return [Microsoft.ML.Transforms.ColumnConcatenator]::new($outputColumn, $inputColumns) } return [Microsoft.ML.Transforms.ColumnConcatenator]::new() } "CopyColumnsTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.CopyColumnsTransformColumn]::new() } "ColumnCopier" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.ColumnCopier]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.ColumnCopier]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.ColumnCopier]::new() } "ColumnDropper" { # Void .ctor() return [Microsoft.ML.Transforms.ColumnDropper]::new() } "ColumnSelector" { # Void .ctor() return [Microsoft.ML.Transforms.ColumnSelector]::new() } "ConvertTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.ConvertTransformColumn]::new() } "ColumnTypeConverter" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.ColumnTypeConverter]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.ColumnTypeConverter]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.ColumnTypeConverter]::new() } "CombinerByContiguousGroupId" { # Void .ctor() return [Microsoft.ML.Transforms.CombinerByContiguousGroupId]::new() } "NormalizeTransformAffineColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NormalizeTransformAffineColumn]::new() } "ConditionalNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.ConditionalNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.ConditionalNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.ConditionalNormalizer]::new() } "DataCache" { # Void .ctor() return [Microsoft.ML.Transforms.DataCache]::new() } "DatasetScorer" { # Void .ctor() return [Microsoft.ML.Transforms.DatasetScorer]::new() } "DatasetTransformScorer" { # Void .ctor() return [Microsoft.ML.Transforms.DatasetTransformScorer]::new() } "TermTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.TermTransformColumn]::new() } "Dictionarizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.Dictionarizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.Dictionarizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.Dictionarizer]::new() } "FeatureCombiner" { # Void .ctor() return [Microsoft.ML.Transforms.FeatureCombiner]::new() } "FeatureSelectorByCount" { # Void .ctor() return [Microsoft.ML.Transforms.FeatureSelectorByCount]::new() } "FeatureSelectorByMutualInformation" { # Void .ctor() return [Microsoft.ML.Transforms.FeatureSelectorByMutualInformation]::new() } "LpNormNormalizerTransformGcnColumn" { # Void .ctor() return [Microsoft.ML.Transforms.LpNormNormalizerTransformGcnColumn]::new() } "GlobalContrastNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.GlobalContrastNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.GlobalContrastNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.GlobalContrastNormalizer]::new() } "HashJoinTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.HashJoinTransformColumn]::new() } "HashConverter" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.HashConverter]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.HashConverter]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.HashConverter]::new() } "KeyToValueTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.KeyToValueTransformColumn]::new() } "KeyToTextConverter" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.KeyToTextConverter]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.KeyToTextConverter]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.KeyToTextConverter]::new() } "LabelColumnKeyBooleanConverter" { # Void .ctor() return [Microsoft.ML.Transforms.LabelColumnKeyBooleanConverter]::new() } "LabelIndicatorTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.LabelIndicatorTransformColumn]::new() } "LabelIndicator" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.LabelIndicator]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.LabelIndicator]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.LabelIndicator]::new() } "LabelToFloatConverter" { # Void .ctor() return [Microsoft.ML.Transforms.LabelToFloatConverter]::new() } "NormalizeTransformLogNormalColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NormalizeTransformLogNormalColumn]::new() } "LogMeanVarianceNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.LogMeanVarianceNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.LogMeanVarianceNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.LogMeanVarianceNormalizer]::new() } "LpNormNormalizerTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.LpNormNormalizerTransformColumn]::new() } "LpNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.LpNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.LpNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.LpNormalizer]::new() } "ManyHeterogeneousModelCombiner" { # Void .ctor() return [Microsoft.ML.Transforms.ManyHeterogeneousModelCombiner]::new() } "MeanVarianceNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MeanVarianceNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MeanVarianceNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MeanVarianceNormalizer]::new() } "MinMaxNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MinMaxNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MinMaxNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MinMaxNormalizer]::new() } "NAHandleTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NAHandleTransformColumn]::new() } "MissingValueHandler" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MissingValueHandler]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MissingValueHandler]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MissingValueHandler]::new() } "NAIndicatorTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NAIndicatorTransformColumn]::new() } "MissingValueIndicator" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MissingValueIndicator]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MissingValueIndicator]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MissingValueIndicator]::new() } "NADropTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NADropTransformColumn]::new() } "MissingValuesDropper" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MissingValuesDropper]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MissingValuesDropper]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MissingValuesDropper]::new() } "MissingValuesRowDropper" { # Void .ctor() return [Microsoft.ML.Transforms.MissingValuesRowDropper]::new() } "NAReplaceTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NAReplaceTransformColumn]::new() } "MissingValueSubstitutor" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.MissingValueSubstitutor]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.MissingValueSubstitutor]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.MissingValueSubstitutor]::new() } "ModelCombiner" { # Void .ctor() return [Microsoft.ML.Transforms.ModelCombiner]::new() } "NgramTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.NgramTransformColumn]::new() } "NGramTranslator" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.NGramTranslator]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.NGramTranslator]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.NGramTranslator]::new() } "NoOperation" { # Void .ctor() return [Microsoft.ML.Transforms.NoOperation]::new() } "OptionalColumnCreator" { # Void .ctor() return [Microsoft.ML.Transforms.OptionalColumnCreator]::new() } "PredictedLabelColumnOriginalValueConverter" { # Void .ctor() return [Microsoft.ML.Transforms.PredictedLabelColumnOriginalValueConverter]::new() } "GenerateNumberTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.GenerateNumberTransformColumn]::new() } "RandomNumberGenerator" { # Void .ctor() return [Microsoft.ML.Transforms.RandomNumberGenerator]::new() } "RowRangeFilter" { # Void .ctor() return [Microsoft.ML.Transforms.RowRangeFilter]::new() } "RowSkipAndTakeFilter" { # Void .ctor() return [Microsoft.ML.Transforms.RowSkipAndTakeFilter]::new() } "RowSkipFilter" { # Void .ctor() return [Microsoft.ML.Transforms.RowSkipFilter]::new() } "RowTakeFilter" { # Void .ctor() return [Microsoft.ML.Transforms.RowTakeFilter]::new() } "ScoreColumnSelector" { # Void .ctor() return [Microsoft.ML.Transforms.ScoreColumnSelector]::new() } "Scorer" { # Void .ctor() return [Microsoft.ML.Transforms.Scorer]::new() } "Segregator" { # Void .ctor() return [Microsoft.ML.Transforms.Segregator]::new() } "SentimentAnalyzer" { # Void .ctor() return [Microsoft.ML.Transforms.SentimentAnalyzer]::new() } "SupervisedBinNormalizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.SupervisedBinNormalizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.SupervisedBinNormalizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.SupervisedBinNormalizer]::new() } "TextTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.TextTransformColumn]::new() } "TermLoaderArguments" { # Void .ctor() return [Microsoft.ML.Transforms.TermLoaderArguments]::new() } "TextFeaturizer" { # Void .ctor() # Void .ctor(System.String, System.String[]) if (($outputColumn) -and ($inputColumns)) { return [Microsoft.ML.Transforms.TextFeaturizer]::new($outputColumn, $inputColumns) } return [Microsoft.ML.Transforms.TextFeaturizer]::new() } "TextToKeyConverter" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.TextToKeyConverter]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.TextToKeyConverter]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.TextToKeyConverter]::new() } "TrainTestDatasetSplitter" { # Void .ctor() return [Microsoft.ML.Transforms.TrainTestDatasetSplitter]::new() } "TreeLeafFeaturizer" { # Void .ctor() return [Microsoft.ML.Transforms.TreeLeafFeaturizer]::new() } "TwoHeterogeneousModelCombiner" { # Void .ctor() return [Microsoft.ML.Transforms.TwoHeterogeneousModelCombiner]::new() } "DelimitedTokenizeTransformColumn" { # Void .ctor() return [Microsoft.ML.Transforms.DelimitedTokenizeTransformColumn]::new() } "WordTokenizer" { # Void .ctor() # Void .ctor(System.String[]) # Void .ctor(System.ValueTuple`2[System.String,System.String][]) if ($inputColumns) { return [Microsoft.ML.Transforms.WordTokenizer]::new($inputColumns) } if ($inputOutputColumns) { return [Microsoft.ML.Transforms.WordTokenizer]::new($inputOutputColumns) } return [Microsoft.ML.Transforms.WordTokenizer]::new() } default { throw "Error: The Specified AmoebaML Transforms $Type not implemented." } } } |