Package deepnetts.eval

Class Evaluators

java.lang.Object

deepnetts.eval.Evaluators

public class Evaluators
extends Object

Utility methods for evaluating machine learning models.

Method Summary

Modifier and Type	Method	Description
static ClassificationMetrics	evaluateClassifier(NeuralNetwork<?> neuralNet, javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet)
static RegressionMetrics	evaluateRegressor(NeuralNetwork<?> neuralNet, javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet)	Evaluates specified neural network with test set, as a regression model and returns basic regression evauation metrics.

Methods inherited from class java.lang.Object

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

Method Details

evaluateRegressor

public static RegressionMetrics evaluateRegressor(NeuralNetwork<?> neuralNet,
 javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet)

Evaluates specified neural network with test set, as a regression model and returns basic regression evauation metrics. Tells you how good the network approximates function described with test set.

Parameters:

neuralNet -

testSet -

Returns:

regression performance measures

See Also:

• EvaluationMetrics

evaluateClassifier

public static ClassificationMetrics evaluateClassifier(NeuralNetwork<?> neuralNet,
 javax.visrec.ml.data.DataSet<? extends MLDataItem> testSet)

Parameters:

neuralNet -

testSet -

Returns:

classification performance measure