134 instantiations of InputOutputColumnPair
Microsoft.ML.AutoML (6)
AutoMlUtils.cs (1)
42res.Add(new InputOutputColumnPair(outputs[i], inputs[i]));
EstimatorExtensions\EstimatorExtensions.cs (5)
113var pair = new InputOutputColumnPair(outColumns[i], inColumns[i]); 140var pair = new InputOutputColumnPair(outColumns[i], inColumns[i]); 188cols[i] = new InputOutputColumnPair(outColumns[i], inColumns[i]); 219cols[i] = new InputOutputColumnPair(outColumns[i], inColumns[i]); 266cols[i] = new InputOutputColumnPair(outColumns[i], inColumns[i]);
Microsoft.ML.Data (1)
Transforms\ExtensionsCatalog.cs (1)
49infos.Select(info => new InputOutputColumnPair(info.outputColumnName, info.inputColumnName)).ToList().AsReadOnly();
Microsoft.ML.Samples (30)
Dynamic\Transforms\Categorical\OneHotEncodingMultiColumn.cs (2)
33new InputOutputColumnPair("Education"), 34new InputOutputColumnPair("ZipCode")
Dynamic\Transforms\Categorical\OneHotHashEncodingMultiColumn.cs (2)
33new InputOutputColumnPair("Education"), 34new InputOutputColumnPair("ZipCode")
Dynamic\Transforms\Conversion\ConvertTypeMultiColumn.cs (4)
42new InputOutputColumnPair("Converted1", "Feature1"), 43new InputOutputColumnPair("Converted2", "Feature2"), 44new InputOutputColumnPair("Converted3", "Feature3"), 45new InputOutputColumnPair("Converted4", "Feature4"),
Dynamic\Transforms\Conversion\MapKeyToValueMultiColumn.cs (2)
48new InputOutputColumnPair("LabelOriginalValue","Label"), 49new InputOutputColumnPair("PredictedLabelOriginalValue",
Dynamic\Transforms\Conversion\MapKeyToVectorMultiColumn.cs (2)
35new InputOutputColumnPair ("TimeframeVector", "Timeframe"), 36new InputOutputColumnPair ("CategoryVector", "Category")
Dynamic\Transforms\Conversion\MapValueToKeyMultiColumn.cs (4)
31new InputOutputColumnPair("StudyTimeCategory", "StudyTime"), 32new InputOutputColumnPair("CourseCategory", "Course") 83new InputOutputColumnPair("StudyTimeCategory", "StudyTime"), 84new InputOutputColumnPair("CourseCategory", "Course")
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCountMultiColumn.cs (2)
41InputOutputColumnPair("NumericVector"), new InputOutputColumnPair(
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnMutualInformationMultiColumn.cs (2)
41{ new InputOutputColumnPair("NumericVectorA"), new 42InputOutputColumnPair("NumericVectorB") }, labelColumnName: "Label",
Dynamic\Transforms\IndicateMissingValuesMultiColumn.cs (2)
36new InputOutputColumnPair("MissingIndicator1", "Features1"), 37new InputOutputColumnPair("MissingIndicator2", "Features2")
Dynamic\Transforms\NormalizeBinningMulticolumn.cs (2)
38new InputOutputColumnPair("Features"), 39new InputOutputColumnPair("Features2"),
Dynamic\Transforms\NormalizeMinMaxMulticolumn.cs (2)
46new InputOutputColumnPair("Features"), 47new InputOutputColumnPair("Features2")
Dynamic\Transforms\ReplaceMissingValuesMultiColumn.cs (4)
37new InputOutputColumnPair("MissingReplaced1", "Features1"), 38new InputOutputColumnPair("MissingReplaced2", "Features2") 72new InputOutputColumnPair("MissingReplaced1", "Features1"), 73new InputOutputColumnPair("MissingReplaced2", "Features2")
Microsoft.ML.TensorFlow.Tests (3)
TensorflowTests.cs (3)
1282new[] { new InputOutputColumnPair("Features", "TokenizedWords") })); 1351.Append(_mlContext.Transforms.CopyColumns(new[] { new InputOutputColumnPair("AOut", "Original_A"), new InputOutputColumnPair("BOut", "Joined_Splited_Text") }));
Microsoft.ML.Tests (92)
OnnxConversionTest.cs (1)
1167var pipeline = mlContext.Transforms.IndicateMissingValues(new[] { new InputOutputColumnPair("MissingIndicator", "Features"), })
Transformers\CountTargetEncodingTests.cs (14)
33new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, "Label"); 64new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, "Label", CountTableBuilderBase.CreateCMCountTableBuilder(2, 1 << 6)); 67estimator = ML.Transforms.CountTargetEncode(new[] { new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, transformer); 85new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, "Label", CountTableBuilderBase.CreateCMCountTableBuilder(2, 1 << 6), laplaceScale: 1f) 93new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, "Label", CountTableBuilderBase.CreateCMCountTableBuilder(2, 1 << 6)) 102new InputOutputColumnPair("ScalarString"), new InputOutputColumnPair("VectorString") }, "Label", CountTableBuilderBase.CreateCMCountTableBuilder(2, 1 << 6)) 170ML.Transforms.CountTargetEncode(new[] { new InputOutputColumnPair("ScalarString1", "ScalarString"), new InputOutputColumnPair("VectorString2", "VectorString") },
Transformers\FeatureSelectionTests.cs (2)
180new InputOutputColumnPair("out1", "VectorFloat"), 181new InputOutputColumnPair("out2", "VectorDouble")
Transformers\KeyToBinaryVectorEstimatorTest.cs (9)
54var pipe = ML.Transforms.Conversion.MapKeyToBinaryVector(new[] { new InputOutputColumnPair("CatA", "TermA"), new InputOutputColumnPair("CatC", "TermC") }); 101new InputOutputColumnPair("CatA", "TA"), 102new InputOutputColumnPair("CatB", "TB"), 103new InputOutputColumnPair("CatC", "TC"), 104new InputOutputColumnPair("CatD", "TD") 155var pipe = ML.Transforms.Conversion.MapKeyToBinaryVector(new[] { new InputOutputColumnPair("CatA", "TermA"), new InputOutputColumnPair("CatB", "TermB"), new InputOutputColumnPair("CatC", "TermC") });
Transformers\NAIndicatorTests.cs (12)
48new InputOutputColumnPair("NAA", "A"), 49new InputOutputColumnPair("NAB", "B"), 50new InputOutputColumnPair("NAC", "C"), 51new InputOutputColumnPair("NAD", "D") 76new InputOutputColumnPair("NAA", "A"), 77new InputOutputColumnPair("NAB", "B"), 78new InputOutputColumnPair("NAC", "C"), 79new InputOutputColumnPair("NAD", "D") 106new InputOutputColumnPair("A", "ScalarFloat"), 107new InputOutputColumnPair("B", "ScalarDouble"), 108new InputOutputColumnPair("C", "VectorFloat"), 109new InputOutputColumnPair("D", "VectorDoulbe")
Transformers\NormalizerTests.cs (28)
239new[] { new InputOutputColumnPair("float1"), new InputOutputColumnPair("float4"), 240new InputOutputColumnPair("double1"), new InputOutputColumnPair("double4"), }) 242new[] {new InputOutputColumnPair("float1bin", "float1"), new InputOutputColumnPair("float4bin", "float4"), 243new InputOutputColumnPair("double1bin", "double1"), new InputOutputColumnPair("double4bin", "double4")})) 245new[] {new InputOutputColumnPair("float1mv", "float1"), new InputOutputColumnPair("float4mv", "float4"), 246new InputOutputColumnPair("double1mv", "double1"), new InputOutputColumnPair("double4mv", "double4")})) 248new[] {new InputOutputColumnPair("float1lmv", "float1"), new InputOutputColumnPair("float4lmv", "float4"), 249new InputOutputColumnPair("double1lmv", "double1"), new InputOutputColumnPair("double4lmv", "double4")})) 251new[] {new InputOutputColumnPair("float1nsb", "float1"), new InputOutputColumnPair("float4nsb", "float4"), 252new InputOutputColumnPair("double1nsb", "double1"), new InputOutputColumnPair("double4nsb", "double4")})); 392new[] {new InputOutputColumnPair("float1rbs", "float1"), new InputOutputColumnPair("float4rbs", "float4"), 393new InputOutputColumnPair("double1rbs", "double1"), new InputOutputColumnPair("double4rbs", "double4")}); 431new[] {new InputOutputColumnPair("float1rbs", "float1"), new InputOutputColumnPair("float4rbs", "float4"), 432new InputOutputColumnPair("double1rbs", "double1"), new InputOutputColumnPair("double4rbs", "double4")}
Transformers\ValueMappingTests.cs (26)
146Append(ML.Transforms.Conversion.MapValue(keyValuePairs, true, new[] { new InputOutputColumnPair("VecD", "TokenizeA"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") })); 371new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 403new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 437var estimator = ML.Transforms.Conversion.MapValue(keyValuePairs, true, new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 478var estimator = ML.Transforms.Conversion.MapValue(keyValuePairs, true, new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 519var estimator = ML.Transforms.Conversion.MapValue(keyValuePairs, true, new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 601var est = ML.Transforms.Conversion.MapValue(keyValuePairs, new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 620var est = ML.Transforms.Conversion.MapValue(keyValuePairs, new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B"), new InputOutputColumnPair("F", "C") }); 693new[] { new InputOutputColumnPair("D", "A"), new InputOutputColumnPair("E", "B") });
Microsoft.ML.Transforms (2)
Dracula\CountTargetEncodingTransformer.cs (2)
151columns.Select(c => new InputOutputColumnPair(c.OutputColumnName, c.OutputColumnName)).ToArray()); 535return new CountTargetEncodingEstimator(CatalogUtils.GetEnvironment(catalog), labelColumn, initialCounts, new[] { new InputOutputColumnPair(outputColumnName, inputColumnName) });
82 references to InputOutputColumnPair
Microsoft.ML.AutoML (9)
AutoMlUtils.cs (2)
32public static InputOutputColumnPair[] CreateInputOutputColumnPairsFromStrings(string[] inputs, string[] outputs) 39var res = new List<InputOutputColumnPair>();
EstimatorExtensions\EstimatorExtensions.cs (7)
110var pairs = new InputOutputColumnPair[inColumns.Length]; 113var pair = new InputOutputColumnPair(outColumns[i], inColumns[i]); 137var pairs = new InputOutputColumnPair[inColumns.Length]; 140var pair = new InputOutputColumnPair(outColumns[i], inColumns[i]); 185var cols = new InputOutputColumnPair[inColumns.Length]; 216var cols = new InputOutputColumnPair[inColumns.Length]; 263var cols = new InputOutputColumnPair[inColumns.Length];
Microsoft.ML.Data (25)
Transforms\ConversionsExtensionsCatalog.cs (14)
101InputOutputColumnPair[] columns, 126/// <see cref="MapValueToKey(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], int, ValueToKeyMappingEstimator.KeyOrdinality, bool, IDataView)"/></remarks> 147/// <see cref="MapValueToKey(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], int, ValueToKeyMappingEstimator.KeyOrdinality, bool, IDataView)"/></remarks> 159public static KeyToValueMappingEstimator MapKeyToValue(this TransformsCatalog.ConversionTransforms catalog, InputOutputColumnPair[] columns) 213InputOutputColumnPair[] columns, bool outputCountVector = KeyToVectorMappingEstimator.Defaults.OutputCountVector) 283InputOutputColumnPair[] columns, 367params InputOutputColumnPair[] columns) 381InputOutputColumnPair.ConvertToValueTuples(columns)); 401params InputOutputColumnPair[] columns) 415InputOutputColumnPair.ConvertToValueTuples(columns)); 471params InputOutputColumnPair[] columns) 485InputOutputColumnPair.ConvertToValueTuples(columns)); 530IDataView lookupMap, DataViewSchema.Column keyColumn, DataViewSchema.Column valueColumn, params InputOutputColumnPair[] columns) 534return new ValueMappingEstimator(env, lookupMap, keyColumn, valueColumn, InputOutputColumnPair.ConvertToValueTuples(columns));
Transforms\ExtensionsCatalog.cs (6)
44internal static (string outputColumnName, string inputColumnName)[] ConvertToValueTuples(InputOutputColumnPair[] infos) => 48internal static IReadOnlyList<InputOutputColumnPair> ConvertFromValueTuples((string outputColumnName, string inputColumnName)[] infos) => 78/// Create a <see cref="ColumnCopyingEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" /> 79/// to a new column: <see cref="InputOutputColumnPair.OutputColumnName" />. 92internal static ColumnCopyingEstimator CopyColumns(this TransformsCatalog catalog, params InputOutputColumnPair[] columns) 96return new ColumnCopyingEstimator(env, InputOutputColumnPair.ConvertToValueTuples(columns));
Transforms\KeyToValue.cs (1)
616/// <seealso cref="ConversionsExtensionsCatalog.MapKeyToValue(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[])"/>
Transforms\KeyToVector.cs (1)
758/// <seealso cref=" ConversionsExtensionsCatalog.MapKeyToVector(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], bool)"/>
Transforms\TypeConverting.cs (1)
531/// <seealso cref="ConversionsExtensionsCatalog.ConvertType(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], DataKind)"/>
Transforms\ValueToKeyMappingEstimator.cs (2)
43/// <seealso cref="ConversionsExtensionsCatalog.MapValueToKey(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], int, KeyOrdinality, bool, IDataView)"/> 45/// <seealso cref="ConversionsExtensionsCatalog.MapValueToKey(TransformsCatalog.ConversionTransforms, InputOutputColumnPair[], int, ValueToKeyMappingEstimator.KeyOrdinality, bool, IDataView)"/>
Microsoft.ML.Experimental (2)
OneToOneTransformerBaseExtensions.cs (2)
15public static IReadOnlyList<InputOutputColumnPair> GetColumnPairs(this OneToOneTransformerBase transformer) => 16InputOutputColumnPair.ConvertFromValueTuples(transformer.ColumnPairs);
Microsoft.ML.ImageAnalytics (6)
ExtensionsCatalog.cs (6)
17/// Create a <see cref="ImageGrayscalingEstimator"/>, which converts images in the column specified in <see cref="InputOutputColumnPair.InputColumnName"/> 18/// to grayscale images in a new column: <see cref="InputOutputColumnPair.OutputColumnName" />. 36/// Create a <see cref="ImageGrayscalingEstimator"/>, which converts images in the column specified in <see cref="InputOutputColumnPair.InputColumnName"/> 37/// to grayscale images in a new column: <see cref="InputOutputColumnPair.OutputColumnName" />. 48internal static ImageGrayscalingEstimator ConvertToGrayscale(this TransformsCatalog catalog, params InputOutputColumnPair[] columns) 52return new ImageGrayscalingEstimator(env, InputOutputColumnPair.ConvertToValueTuples(columns));
Microsoft.ML.Samples (2)
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCountMultiColumn.cs (1)
40.SelectFeaturesBasedOnCount(new InputOutputColumnPair[] { new
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnMutualInformationMultiColumn.cs (1)
40.SelectFeaturesBasedOnMutualInformation(new InputOutputColumnPair[]
Microsoft.ML.Transforms (38)
CategoricalCatalog.cs (2)
78InputOutputColumnPair[] columns, 177InputOutputColumnPair[] columns,
ConversionsCatalog.cs (2)
25params InputOutputColumnPair[] columns) 29return new KeyToBinaryVectorMappingEstimator(env, InputOutputColumnPair.ConvertToValueTuples(columns));
CountFeatureSelection.cs (1)
65/// <seealso cref="FeatureSelectionCatalog.SelectFeaturesBasedOnCount(TransformsCatalog.FeatureSelectionTransforms, InputOutputColumnPair[], long)"/>
Dracula\CountTableTransformer.cs (2)
96internal CountTableEstimator(IHostEnvironment env, string labelColumnName, CountTableTransformer initial, params InputOutputColumnPair[] columns) 102private static ColumnOptionsBase[] ExtractColumnOptions(CountTableTransformer initial, InputOutputColumnPair[] columns)
Dracula\CountTargetEncodingTransformer.cs (7)
45/// <seealso cref="CountTargetEncodingCatalog.CountTargetEncode(TransformsCatalog, InputOutputColumnPair[], CountTargetEncodingTransformer, string)" /> 46/// <seealso cref="CountTargetEncodingCatalog.CountTargetEncode(TransformsCatalog, InputOutputColumnPair[], string, CountTableBuilderBase, float, float, bool, int, bool, uint)" /> 141internal CountTargetEncodingEstimator(IHostEnvironment env, string labelColumnName, CountTargetEncodingTransformer initialCounts, params InputOutputColumnPair[] columns) 220internal static CountTableEstimator LoadFromFile(IHostEnvironment env, string initialCountsModel, string labelColumn, InputOutputColumnPair[] columns) 404internal bool VerifyColumns(InputOutputColumnPair[] columns) 432InputOutputColumnPair[] columns, string labelColumn = DefaultColumnNames.Label, 480InputOutputColumnPair[] columns, CountTargetEncodingTransformer initialCounts, string labelColumn = "Label")
ExtensionsCatalog.cs (6)
40/// Create a <see cref="MissingValueIndicatorEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" /> 41/// to a new column: <see cref="InputOutputColumnPair.OutputColumnName" />. 52public static MissingValueIndicatorEstimator IndicateMissingValues(this TransformsCatalog catalog, InputOutputColumnPair[] columns) 86/// Create a <see cref="ColumnCopyingEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" /> 87/// to a new column: <see cref="InputOutputColumnPair.OutputColumnName" /> and replaces missing values in it according to <paramref name="replacementMode"/>. 103InputOutputColumnPair[] columns,
FeatureSelectionCatalog.cs (2)
60InputOutputColumnPair[] columns, 119InputOutputColumnPair[] columns,
MissingValueIndicatorTransformer.cs (1)
505/// <seealso cref="ExtensionsCatalog.IndicateMissingValues(TransformsCatalog, InputOutputColumnPair[])" />
MissingValueReplacing.cs (1)
925/// <seealso cref="ExtensionsCatalog.ReplaceMissingValues(TransformsCatalog, InputOutputColumnPair[], ReplacementMode, bool)" />
MutualInformationFeatureSelection.cs (1)
70/// <seealso cref="FeatureSelectionCatalog.SelectFeaturesBasedOnMutualInformation(TransformsCatalog.FeatureSelectionTransforms, InputOutputColumnPair[], string, int, int)"/>
NormalizerCatalog.cs (9)
27params InputOutputColumnPair[] columns) 31return new NormalizingEstimator(env, mode, InputOutputColumnPair.ConvertToValueTuples(columns)); 76public static NormalizingEstimator NormalizeMinMax(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 121public static NormalizingEstimator NormalizeMeanVariance(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 164public static NormalizingEstimator NormalizeLogMeanVariance(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 210public static NormalizingEstimator NormalizeLogMeanVariance(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 263public static NormalizingEstimator NormalizeBinning(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 315public static NormalizingEstimator NormalizeSupervisedBinning(this TransformsCatalog catalog, InputOutputColumnPair[] columns, 376public static NormalizingEstimator NormalizeRobustScaling(this TransformsCatalog catalog, InputOutputColumnPair[] columns,
OneHotEncoding.cs (1)
194/// <seealso cref="CategoricalCatalog.OneHotEncoding(TransformsCatalog.CategoricalTransforms, InputOutputColumnPair[], OneHotEncodingEstimator.OutputKind, int, ValueToKeyMappingEstimator.KeyOrdinality, IDataView)"/>
OneHotHashEncoding.cs (1)
250/// <seealso cref="CategoricalCatalog.OneHotHashEncoding(TransformsCatalog.CategoricalTransforms, InputOutputColumnPair[], OneHotEncodingEstimator.OutputKind, int, uint, bool, int)"/>
Text\TextCatalog.cs (2)
106params InputOutputColumnPair[] columns) 110return new TokenizingByCharactersEstimator(env, useMarkerCharacters, InputOutputColumnPair.ConvertToValueTuples(columns));