Class  Description 

BinaryClassificationEvaluator 
Evaluator for binary classification, which expects input columns rawPrediction, label and
an optional weight column.

ClusteringEvaluator 
Evaluator for clustering results.

ClusteringMetrics 
Metrics for clustering, which expects two input columns: prediction and label.

CosineSilhouette 
The algorithm which is implemented in this object, instead, is an efficient and parallel
implementation of the Silhouette using the cosine distance measure.

Evaluator 
Abstract class for evaluators that compute metrics from predictions.

MulticlassClassificationEvaluator 
Evaluator for multiclass classification, which expects input columns: prediction, label,
weight (optional) and probability (only for logLoss).

MultilabelClassificationEvaluator 
:: Experimental ::
Evaluator for multilabel classification, which expects two input
columns: prediction and label.

RankingEvaluator 
:: Experimental ::
Evaluator for ranking, which expects two input columns: prediction and label.

RegressionEvaluator 
Evaluator for regression, which expects input columns prediction, label and
an optional weight column.

SquaredEuclideanSilhouette 
SquaredEuclideanSilhouette computes the average of the
Silhouette over all the data of the dataset, which is
a measure of how appropriately the data have been clustered.

SquaredEuclideanSilhouette.ClusterStats  
SquaredEuclideanSilhouette.ClusterStats$ 