1 write to InputColumnName
Microsoft.ML.Data (1)
Transforms\ExtensionsCatalog.cs (1)
39InputColumnName = inputColumnName ?? outputColumnName;
29 references to InputColumnName
Microsoft.ML.Data (7)
Transforms\ConversionsExtensionsCatalog.cs (4)
106var columnOptions = columns.Select(x => new TypeConvertingEstimator.ColumnOptions(x.OutputColumnName, outputKind, x.InputColumnName)).ToArray(); 163return new KeyToValueMappingEstimator(env, columns.Select(x => (x.OutputColumnName, x.InputColumnName)).ToArray()); 217var columnOptions = columns.Select(x => new KeyToVectorMappingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, outputCountVector)).ToArray(); 291var columnOptions = columns.Select(x => new ValueToKeyMappingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, maximumNumberOfKeys, keyOrdinality, addKeyValueAnnotationsAsText)).ToArray();
Transforms\ExtensionsCatalog.cs (3)
27/// Name of the column resulting from the transformation of <see cref="InputColumnName"/>. 45infos.Select(info => (info.OutputColumnName, info.InputColumnName)).ToArray(); 78/// Create a <see cref="ColumnCopyingEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" />
Microsoft.ML.ImageAnalytics (2)
ExtensionsCatalog.cs (2)
17/// Create a <see cref="ImageGrayscalingEstimator"/>, which converts images in the column specified in <see cref="InputOutputColumnPair.InputColumnName"/> 36/// Create a <see cref="ImageGrayscalingEstimator"/>, which converts images in the column specified in <see cref="InputOutputColumnPair.InputColumnName"/>
Microsoft.ML.Tests (1)
Transformers\NormalizerTests.cs (1)
647Assert.Equal("input", t.GetColumnPairs()[0].InputColumnName);
Microsoft.ML.Transforms (19)
CategoricalCatalog.cs (2)
86var columnOptions = columns.Select(x => new OneHotEncodingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, outputKind, maximumNumberOfKeys, keyOrdinality)).ToArray(); 186var columnOptions = columns.Select(x => new OneHotHashEncodingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, outputKind, numberOfBits, seed, useOrderedHashing, maximumNumberOfInverts)).ToArray();
Dracula\CountTableTransformer.cs (1)
110cols[i] = new SharedColumnOptions(columns[i].OutputColumnName, columns[i].InputColumnName,
Dracula\CountTargetEncodingTransformer.cs (3)
406return columns.All(c => HashingTransformer.Columns.Select(hc => hc.InputColumnName).Contains(c.InputColumnName)) 453columns[i].OutputColumnName, columns[i].InputColumnName, priorCoefficient, laplaceScale); 463columns[i].OutputColumnName, columns[i].InputColumnName, builder, priorCoefficient, laplaceScale);
ExtensionsCatalog.cs (4)
40/// Create a <see cref="MissingValueIndicatorEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" /> 56return new MissingValueIndicatorEstimator(env, columns.Select(x => (x.OutputColumnName, x.InputColumnName)).ToArray()); 86/// Create a <see cref="ColumnCopyingEstimator"/>, which copies the data from the column specified in <see cref="InputOutputColumnPair.InputColumnName" /> 109var columnOptions = columns.Select(x => new MissingValueReplacingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, replacementMode, imputeBySlot)).ToArray();
FeatureSelectionCatalog.cs (2)
68columns.Select(x => (x.OutputColumnName, x.InputColumnName)).ToArray()); 124var columnOptions = columns.Select(x => new CountFeatureSelectingEstimator.ColumnOptions(x.OutputColumnName, x.InputColumnName, count)).ToArray();
NormalizerCatalog.cs (7)
81new NormalizingEstimator.MinMaxColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, fixZero)).ToArray()); 127new NormalizingEstimator.MeanVarianceColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, fixZero, useCdf)).ToArray()); 169new NormalizingEstimator.LogMeanVarianceColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, useCdf, false)).ToArray()); 216new NormalizingEstimator.LogMeanVarianceColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, useCdf, fixZero)).ToArray()); 269new NormalizingEstimator.BinningColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, fixZero, maximumBinCount)).ToArray()); 324column.OutputColumnName, column.InputColumnName, labelColumnName, maximumExampleCount, fixZero, maximumBinCount, mininimumExamplesPerBin)).ToArray()); 383new NormalizingEstimator.RobustScalingColumnOptions(column.OutputColumnName, column.InputColumnName, maximumExampleCount, centerData, quantileMin, quantileMax)).ToArray());