Uses of Class
deepnetts.eval.ClassificationMetrics

Packages that use ClassificationMetrics

Package	Description
deepnetts.eval	Evaluation procedures for machine learning models, used to estimate how good models are performing when given new data that (that was not used for training).

Uses of ClassificationMetrics in deepnetts.eval

Methods in deepnetts.eval that return ClassificationMetrics

Modifier and Type	Method and Description
static ClassificationMetrics[]	ClassificationMetrics.createFrom(ConfusionMatrix confusionMatrix) Creates classification metrics from the given confusion matrix.
ClassificationMetrics	ClassifierEvaluator.evaluate(NeuralNetwork neuralNet, javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet) Performs classifier evaluation and returns classification performance metrics.
static ClassificationMetrics	Evaluators.evaluateClassifier(NeuralNetwork<?> neuralNet, javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet)
ClassificationMetrics	ClassifierEvaluator.getMacroAverage()

Methods in deepnetts.eval that return types with arguments of type ClassificationMetrics

Modifier and Type	Method and Description
Map<String,ClassificationMetrics>	ClassifierEvaluator.getMetricsByClass()

Methods in deepnetts.eval with parameters of type ClassificationMetrics

Modifier and Type	Method and Description
static ClassificationMetrics.Stats	ClassificationMetrics.average(ClassificationMetrics[] results)