BinaryClassificationMetrics BinaryClassificationMetrics BinaryClassificationMetrics Class

Definition

Evaluation results for binary classifiers, excluding probabilistic metrics.

public class BinaryClassificationMetrics
type BinaryClassificationMetrics = class
Public Class BinaryClassificationMetrics
Inheritance
BinaryClassificationMetricsBinaryClassificationMetricsBinaryClassificationMetrics
Derived

Properties

Accuracy Accuracy Accuracy

Gets the accuracy of a classifier which is the proportion of correct predictions in the test set.

AreaUnderPrecisionRecallCurve AreaUnderPrecisionRecallCurve AreaUnderPrecisionRecallCurve

Gets the area under the precision/recall curve of the classifier.

AreaUnderRocCurve AreaUnderRocCurve AreaUnderRocCurve

Gets the area under the ROC curve.

ConfusionMatrix ConfusionMatrix ConfusionMatrix

The confusion matrix giving the counts of the true positives, true negatives, false positives and false negatives for the two classes of data.

F1Score F1Score F1Score

Gets the F1 score of the classifier.

NegativePrecision NegativePrecision NegativePrecision

Gets the negative precision of a classifier which is the proportion of correctly predicted negative instances among all the negative predictions (i.e., the number of negative instances predicted as negative, divided by the total number of instances predicted as negative).

NegativeRecall NegativeRecall NegativeRecall

Gets the negative recall of a classifier which is the proportion of correctly predicted negative instances among all the negative instances (i.e., the number of negative instances predicted as negative, divided by the total number of negative instances).

PositivePrecision PositivePrecision PositivePrecision

Gets the positive precision of a classifier which is the proportion of correctly predicted positive instances among all the positive predictions (i.e., the number of positive instances predicted as positive, divided by the total number of instances predicted as positive).

PositiveRecall PositiveRecall PositiveRecall

Gets the positive recall of a classifier which is the proportion of correctly predicted positive instances among all the positive instances (i.e., the number of positive instances predicted as positive, divided by the total number of positive instances).

Applies to