Package org.elasticsearch.client.ml.dataframe.evaluation.classification

Class Summary Class Description AccuracyMetric AccuracyMetric
is a metric that answers the following two questions: 1.AccuracyMetric.Result AucRocMetric Area under the curve (AUC) of the receiver operating characteristic (ROC).Classification Evaluation of classification results.MulticlassConfusionMatrixMetric Calculates the multiclass confusion matrix.MulticlassConfusionMatrixMetric.ActualClass MulticlassConfusionMatrixMetric.PredictedClass MulticlassConfusionMatrixMetric.Result PerClassSingleValue PrecisionMetric PrecisionMetric
is a metric that answers the question: "What fraction of documents classified as X actually belongs to X?" for any given class X equation: precision(X) = TP(X) / (TP(X) + FP(X)) where: TP(X)  number of true positives wrt X FP(X)  number of false positives wrt XPrecisionMetric.Result RecallMetric RecallMetric
is a metric that answers the question: "What fraction of documents belonging to X have been predicted as X by the classifier?" for any given class X equation: recall(X) = TP(X) / (TP(X) + FN(X)) where: TP(X)  number of true positives wrt X FN(X)  number of false negatives wrt XRecallMetric.Result