Uses of Class
org.deeplearning4j.eval.EvaluationAveraging

Packages that use EvaluationAveraging

Package	Description
org.deeplearning4j.eval

Uses of EvaluationAveraging in org.deeplearning4j.eval

Methods in org.deeplearning4j.eval that return EvaluationAveraging

Modifier and Type	Method and Description
static EvaluationAveraging	EvaluationAveraging.valueOf(String name) Returns the enum constant of this type with the specified name.
static EvaluationAveraging[]	EvaluationAveraging.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.deeplearning4j.eval with parameters of type EvaluationAveraging

Modifier and Type	Method and Description
double	Evaluation.f1(EvaluationAveraging averaging) Calculate the average F1 score across all classes, using macro or micro averaging
double	Evaluation.falseNegativeRate(EvaluationAveraging averaging) Calculate the average false negative rate for all classes - can specify whether macro or micro averaging should be used
double	Evaluation.falsePositiveRate(EvaluationAveraging averaging) Calculate the average false positive rate across all classes.
double	Evaluation.fBeta(double beta, EvaluationAveraging averaging) Calculate the average F_beta score across all classes, using macro or micro averaging
double	Evaluation.gMeasure(EvaluationAveraging averaging) Calculates the average G measure for all outputs using micro or macro averaging
double	Evaluation.matthewsCorrelation(EvaluationAveraging averaging) Calculate the average binary Mathews correlation coefficient, using macro or micro averaging. MCC = (TP*TN - FP*FN) / sqrt((TP+FP)(TP+FN)(TN+FP)(TN+FN)) Note: This is NOT the same as the multi-class Matthews correlation coefficient
double	Evaluation.precision(EvaluationAveraging averaging) Calculate the average precision for all classes.
double	Evaluation.recall(EvaluationAveraging averaging) Calculate the average recall for all classes - can specify whether macro or micro averaging should be used NOTE: if any classes have tp=0 and fn=0, (recall=0/0) these are excluded from the average