BinaryClassificationMetrics Class
Definition
Evaluation results for binary classifiers, excluding probabilistic metrics.
public class BinaryClassificationMetrics
type BinaryClassificationMetrics = class
Public Class BinaryClassificationMetrics
 Inheritance

BinaryClassificationMetrics
 Derived
Properties
Accuracy 
Gets the accuracy of a classifier which is the proportion of correct predictions in the test set. 
AreaUnderPrecisionRecallCurve 
Gets the area under the precision/recall curve of the classifier. 
AreaUnderRocCurve 
Gets the area under the ROC curve. 
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 
Gets the F1 score of the classifier, which is a measure of the classifier's quality considering both precision and recall. 
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 
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 
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 
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). 