de.jungblut.online.regression.multinomial

Class MultinomialRegressionLearner

java.lang.Object

de.jungblut.online.ml.AbstractOnlineLearner<MultinomialRegressionModel>

de.jungblut.online.regression.multinomial.MultinomialRegressionLearner

All Implemented Interfaces:

OnlineLearner<MultinomialRegressionModel>

public class MultinomialRegressionLearner
extends AbstractOnlineLearner<MultinomialRegressionModel>

A regression learner that learns multiple independent regression models and blends them into a single model.

Author:

thomas.jungblut

Field Summary

Fields inherited from class de.jungblut.online.ml.AbstractOnlineLearner

featureDimension, numOutcomeClasses, outcomeDimension, streamSupplier, verbose

Constructor Summary

Constructors

Constructor and Description
MultinomialRegressionLearner(java.util.function.IntFunction<RegressionLearner> learnerFactory)
MultinomialRegressionLearner(StochasticMinimizer minimizer, de.jungblut.math.activation.ActivationFunction activationFunction, de.jungblut.math.loss.LossFunction lossFunction)

Method Summary

Modifier and Type	Method and Description
MultinomialRegressionModel	train(java.util.function.Supplier<java.util.stream.Stream<de.jungblut.online.ml.FeatureOutcomePair>> streamSupplier) Trains a new model using the supplied streams.

Methods inherited from class de.jungblut.online.ml.AbstractOnlineLearner

init, peekDimensions, setVerbose, verbose

Methods inherited from class java.lang.Object

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

Constructor Detail

MultinomialRegressionLearner

public MultinomialRegressionLearner(StochasticMinimizer minimizer,
                                    de.jungblut.math.activation.ActivationFunction activationFunction,
                                    de.jungblut.math.loss.LossFunction lossFunction)

MultinomialRegressionLearner

public MultinomialRegressionLearner(java.util.function.IntFunction<RegressionLearner> learnerFactory)

Method Detail

train

public MultinomialRegressionModel train(java.util.function.Supplier<java.util.stream.Stream<de.jungblut.online.ml.FeatureOutcomePair>> streamSupplier)

Description copied from interface: OnlineLearner

Trains a new model using the supplied streams. In case an algorithm needs multiple iterations, it simply gets a new one from the supplier.

Parameters:

streamSupplier - the supplier that creates a new stream that can be consumed.

Returns:

the trained model.