// Factory method for SignatureDataTransform. internal static IDataTransform Create(IHostEnvironment env, Options options, IDataView input) { Contracts.CheckValue(env, nameof(env)); env.CheckValue(options, nameof(options)); env.CheckUserArg(Utils.Size(options.Columns) > 0, nameof(options.Columns)); var estimator = new CountTargetEncodingEstimator(env, options); return((estimator.Fit(input) as ITransformerWithDifferentMappingAtTrainingTime).TransformForTrainingPipeline(input) as IDataTransform); }
internal static CommonOutputs.TransformOutput Create(IHostEnvironment env, CountTargetEncodingEstimator.Options input) { Contracts.CheckValue(env, nameof(env)); env.CheckValue(input, nameof(input)); var h = EntryPointUtils.CheckArgsAndCreateHost(env, nameof(CountTargetEncoder), input); var view = CountTargetEncodingEstimator.Create(h, input, input.Data); return(new CommonOutputs.TransformOutput() { Model = new TransformModelImpl(h, view, input.Data), OutputData = view }); }
/// <summary> /// Transforms a categorical column into a set of features that includes the count of each label class, /// the log-odds for each label class and the back-off indicator. /// </summary> /// <param name="catalog">The transforms catalog.</param> /// <param name="columns">The input and output columns.</param> /// <param name="labelColumn">The name of the label column.</param> /// <param name="builder">The builder that creates the count tables from the training data.</param> /// <param name="priorCoefficient">The coefficient with which to apply the prior smoothing to the features.</param> /// <param name="laplaceScale">The Laplacian noise diversity/scale-parameter. Recommended values are between 0 and 1. Note that the noise /// will only be applied if the estimator is part of an <see cref="EstimatorChain{TLastTransformer}"/>, when fitting the next estimator in the chain.</param> /// <param name="sharedTable">Indicates whether to keep counts for all columns and slots in one shared count table. If true, the keys in the count table /// will include a hash of the column and slot indices.</param> /// <param name="numberOfBits">The number of bits to hash the input into. Must be between 1 and 31, inclusive.</param> /// <param name="combine">In case the input is a vector column, indicates whether the values should be combined into a single hash to create a single /// count table, or be left as a vector of hashes with multiple count tables.</param> /// <param name="hashingSeed">The seed used for hashing the input columns.</param> /// <returns></returns> public static CountTargetEncodingEstimator CountTargetEncode(this TransformsCatalog catalog, InputOutputColumnPair[] columns, string labelColumn = DefaultColumnNames.Label, CountTableBuilderBase builder = null, float priorCoefficient = CountTableTransformer.Defaults.PriorCoefficient, float laplaceScale = CountTableTransformer.Defaults.LaplaceScale, bool sharedTable = CountTableTransformer.Defaults.SharedTable, int numberOfBits = HashingEstimator.Defaults.NumberOfBits, bool combine = HashingEstimator.Defaults.Combine, uint hashingSeed = HashingEstimator.Defaults.Seed) { var env = CatalogUtils.GetEnvironment(catalog); env.CheckValue(columns, nameof(columns)); builder = builder ?? new CMCountTableBuilder(); CountTargetEncodingEstimator estimator; if (sharedTable) { var columnOptions = new CountTableEstimator.SharedColumnOptions[columns.Length]; for (int i = 0; i < columns.Length; i++) { columnOptions[i] = new CountTableEstimator.SharedColumnOptions( columns[i].OutputColumnName, columns[i].InputColumnName, priorCoefficient, laplaceScale); } estimator = new CountTargetEncodingEstimator(env, labelColumn, columnOptions, builder, numberOfBits, combine, hashingSeed); } else { var columnOptions = new CountTableEstimator.ColumnOptions[columns.Length]; for (int i = 0; i < columns.Length; i++) { columnOptions[i] = new CountTableEstimator.ColumnOptions( columns[i].OutputColumnName, columns[i].InputColumnName, builder, priorCoefficient, laplaceScale); } estimator = new CountTargetEncodingEstimator(env, labelColumn, columnOptions, numberOfBits: numberOfBits, combine: combine, hashingSeed: hashingSeed); } return(estimator); }