PermutationFeatureImportance(
this MulticlassClassificationCatalog catalog,
ITransformer model,
IDataView data,
string labelColumnName = DefaultColumnNames.Label,
bool useFeatureWeightFilter = false,
int?numberOfExamplesToUse = null,
int permutationCount = 1)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = catalog.GetEnvironment();
Contracts.CheckValue(env, nameof(env));
env.CheckValue(data, nameof(data));
env.CheckValue(model, nameof(model));
MulticlassClassificationMetricsStatistics resultInitializer() => new();
MulticlassClassificationMetrics evaluationFunc(IDataView idv) => catalog.Evaluate(idv, labelColumnName);
return(PermutationFeatureImportance(
env,
model,
data,
resultInitializer,
evaluationFunc,
MulticlassClassificationDelta,
permutationCount,
useFeatureWeightFilter,
numberOfExamplesToUse
));
}
PermutationFeatureImportance <TModel>(
this MulticlassClassificationCatalog catalog,
IPredictionTransformer <TModel> model,
IDataView data,
string label = DefaultColumnNames.Label,
string features = DefaultColumnNames.Features,
bool useFeatureWeightFilter = false,
int?topExamples = null,
int permutationCount = 1)
{
return(PermutationFeatureImportance <TModel, MultiClassClassifierMetrics, MultiClassClassifierMetricsStatistics> .GetImportanceMetricsMatrix(
catalog.GetEnvironment(),
model,
data,
idv => catalog.Evaluate(idv, label),
MulticlassClassificationDelta,
features,
permutationCount,
useFeatureWeightFilter,
topExamples));
}
PermutationFeatureImportance <TModel>(
this MulticlassClassificationCatalog catalog,
ISingleFeaturePredictionTransformer <TModel> predictionTransformer,
IDataView data,
string labelColumnName = DefaultColumnNames.Label,
bool useFeatureWeightFilter = false,
int?numberOfExamplesToUse = null,
int permutationCount = 1) where TModel : class
{
return(PermutationFeatureImportance <TModel, MulticlassClassificationMetrics, MulticlassClassificationMetricsStatistics> .GetImportanceMetricsMatrix(
catalog.GetEnvironment(),
predictionTransformer,
data,
() => new MulticlassClassificationMetricsStatistics(),
idv => catalog.Evaluate(idv, labelColumnName),
MulticlassClassificationDelta,
predictionTransformer.FeatureColumnName,
permutationCount,
useFeatureWeightFilter,
numberOfExamplesToUse));
}