/// <summary>
/// Feature Contribution Calculation computes model-specific contribution scores for each feature.
/// Note that this functionality is not supported by all the models. See <see cref="FeatureContributionCalculatingTransformer"/> for a list of the suported models.
/// </summary>
/// <param name="env">The environment to use.</param>
/// <param name="modelParameters">Trained model parameters that support Feature Contribution Calculation and which will be used for scoring.</param>
/// <param name="featureColumnName">The name of the feature column that will be used as input.</param>
/// <param name="numberOfPositiveContributions">The number of positive contributions to report, sorted from highest magnitude to lowest magnitude.
/// Note that if there are fewer features with positive contributions than <paramref name="numberOfPositiveContributions"/>, the rest will be returned as zeros.</param>
/// <param name="numberOfNegativeContributions">The number of negative contributions to report, sorted from highest magnitude to lowest magnitude.
/// Note that if there are fewer features with negative contributions than <paramref name="numberOfNegativeContributions"/>, the rest will be returned as zeros.</param>
/// <param name="normalize">Whether the feature contributions should be normalized to the [-1, 1] interval.</param>
internal FeatureContributionCalculatingTransformer(IHostEnvironment env, ICalculateFeatureContribution modelParameters,
string featureColumnName = DefaultColumnNames.Features,
int numberOfPositiveContributions = FeatureContributionCalculatingEstimator.Defaults.NumberOfPositiveContributions,
int numberOfNegativeContributions = FeatureContributionCalculatingEstimator.Defaults.NumberOfNegativeContributions,
bool normalize = FeatureContributionCalculatingEstimator.Defaults.Normalize)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(FeatureContributionCalculatingTransformer)), new[] { (name: DefaultColumnNames.FeatureContributions, source: featureColumnName) })
/// <summary>
/// Feature Contribution Calculation computes model-specific contribution scores for each feature.
/// Note that this functionality is not supported by all the models. See <see cref="FeatureContributionCalculatingTransformer"/> for a list of the suported models.
/// </summary>
/// <param name="env">The environment to use.</param>
/// <param name="modelParameters">Trained model parameters that support Feature Contribution Calculation and which will be used for scoring.</param>
/// <param name="featureColumn">The name of the feature column that will be used as input.</param>
/// <param name="numPositiveContributions">The number of positive contributions to report, sorted from highest magnitude to lowest magnitude.
/// Note that if there are fewer features with positive contributions than <paramref name="numPositiveContributions"/>, the rest will be returned as zeros.</param>
/// <param name="numNegativeContributions">The number of negative contributions to report, sorted from highest magnitude to lowest magnitude.
/// Note that if there are fewer features with negative contributions than <paramref name="numNegativeContributions"/>, the rest will be returned as zeros.</param>
/// <param name="normalize">Whether the feature contributions should be normalized to the [-1, 1] interval.</param>
public FeatureContributionCalculatingTransformer(IHostEnvironment env, ICalculateFeatureContribution modelParameters,
string featureColumn = DefaultColumnNames.Features,
int numPositiveContributions = FeatureContributionCalculatingEstimator.Defaults.NumPositiveContributions,
int numNegativeContributions = FeatureContributionCalculatingEstimator.Defaults.NumNegativeContributions,
bool normalize = FeatureContributionCalculatingEstimator.Defaults.Normalize)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(FeatureContributionCalculatingTransformer)), new[] { (input: featureColumn, output: DefaultColumnNames.FeatureContributions) })
/// <summary>
/// Feature Contribution Calculation computes model-specific contribution scores for each feature.
/// Note that this functionality is not supported by all the models. See <see cref="FeatureContributionCalculatingTransformer"/> for a list of the suported models.
/// </summary>
/// <param name="catalog">The model explainability operations catalog.</param>
/// <param name="modelParameters">Trained model parameters that support Feature Contribution Calculation and which will be used for scoring.</param>
/// <param name="featureColumn">The name of the feature column that will be used as input.</param>
/// <param name="top">The number of features with highest positive contributions for each data sample that will be retained in the FeatureContribution column.
/// Note that if there are fewer features with positive contributions than <paramref name="top"/>, the rest will be returned as zeros.</param>
/// <param name="bottom">The number of features with least negative contributions for each data sample that will be retained in the FeatureContribution column.
/// Note that if there are fewer features with negative contributions than <paramref name="bottom"/>, the rest will be returned as zeros.</param>
/// <param name="normalize">Whether the feature contributions should be normalized to the [-1, 1] interval.</param>
public static FeatureContributionCalculatingEstimator FeatureContributionCalculation(this ModelOperationsCatalog.ExplainabilityTransforms catalog,
ICalculateFeatureContribution modelParameters,
string featureColumn = DefaultColumnNames.Features,
int top = FeatureContributionDefaults.Top,
int bottom = FeatureContributionDefaults.Bottom,
bool normalize = FeatureContributionDefaults.Normalize)
=> new FeatureContributionCalculatingEstimator(CatalogUtils.GetEnvironment(catalog), modelParameters, featureColumn, top, bottom, normalize);
