Package org.elasticsearch.client.ml.dataframe.evaluation.classification
package org.elasticsearch.client.ml.dataframe.evaluation.classification
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ClassDescription
AccuracyMetric
is a metric that answers the following two questions: 1.Area under the curve (AUC) of the receiver operating characteristic (ROC).Evaluation of classification results.Calculates the multiclass confusion matrix.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 XRecallMetric
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 X