/// <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="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName"/>.</param>
/// <param name="initialCounts">A previously trained count table containing initial counts.</param>
/// <param name="inputColumnName">Name of the column to transform. If set to <see langword="null"/>, the value of the <paramref name="outputColumnName"/> will be used as source.</param>
/// <param name="labelColumn">The name of the label column.</param>
/// <returns></returns>
public static CountTargetEncodingEstimator CountTargetEncode(this TransformsCatalog catalog, string outputColumnName,
CountTargetEncodingTransformer initialCounts,
string inputColumnName = null, string labelColumn = "Label")
{
return(new CountTargetEncodingEstimator(CatalogUtils.GetEnvironment(catalog), labelColumn, initialCounts, new[] { new InputOutputColumnPair(outputColumnName, inputColumnName) }));
}
/// <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="initialCounts">A previously trained count table containing initial counts.</param>
/// <param name="labelColumn">The name of the label column.</param>
/// <returns></returns>
public static CountTargetEncodingEstimator CountTargetEncode(this TransformsCatalog catalog,
InputOutputColumnPair[] columns, CountTargetEncodingTransformer initialCounts, string labelColumn = "Label")
{
return(new CountTargetEncodingEstimator(CatalogUtils.GetEnvironment(catalog), labelColumn, initialCounts, columns));
}
