Uses of Class
deepnetts.eval.ClassificationMetrics
Packages that use ClassificationMetrics
Package
Description
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).
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Uses of ClassificationMetrics in deepnetts.eval
Methods in deepnetts.eval that return ClassificationMetricsModifier and TypeMethodDescriptionstatic ClassificationMetrics[]
ClassificationMetrics.createFrom
(ConfusionMatrix confusionMatrix) Creates classification metrics from the given confusion matrix.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) ClassifierEvaluator.getMacroAverage()
Methods in deepnetts.eval that return types with arguments of type ClassificationMetricsMethods in deepnetts.eval with parameters of type ClassificationMetricsModifier and TypeMethodDescriptionstatic ClassificationMetrics.Stats
ClassificationMetrics.average
(ClassificationMetrics[] results)