Class KFoldCrossValidation

java.lang.Object

deepnetts.net.train.KFoldCrossValidation

public class KFoldCrossValidation
extends Object

Split data set into k parts of equal sizes (folds), then train model with k-1 folds, and validate with remaining 1 fold. Repeat that k times each with different validation fold. Commonly used technique to estimate generalization ability of the model.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	KFoldCrossValidation.Builder	Builder object for KFoldCrossValidation.

Method Summary

Modifier and Type	Method	Description
static KFoldCrossValidation.Builder	builder()
NeuralNetwork	getBestNetwork()
javax.visrec.ml.eval.EvaluationMetrics	getBestResult()
javax.visrec.ml.eval.EvaluationMetrics	getMacroAverage()
TrainingListener	getTrainingListener()
List<TrainingResult>	getTrainingResults()
void	run()

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

run

public void run()

builder

public static KFoldCrossValidation.Builder builder()

getBestResult

public javax.visrec.ml.eval.EvaluationMetrics getBestResult()

getMacroAverage

public javax.visrec.ml.eval.EvaluationMetrics getMacroAverage()

getBestNetwork

public NeuralNetwork getBestNetwork()

getTrainingResults

public List<TrainingResult> getTrainingResults()

getTrainingListener

public TrainingListener getTrainingListener()