org.apache.ignite.ml.naivebayes.gaussian

Class GaussianNaiveBayesTrainer

java.lang.Object

org.apache.ignite.ml.trainers.DatasetTrainer<M,Double>

org.apache.ignite.ml.trainers.SingleLabelDatasetTrainer<GaussianNaiveBayesModel>

org.apache.ignite.ml.naivebayes.gaussian.GaussianNaiveBayesTrainer

public class GaussianNaiveBayesTrainer
extends SingleLabelDatasetTrainer<GaussianNaiveBayesModel>

Trainer for the naive Bayes classification model. The trainer calculates prior probabilities from the input dataset. Prior probabilities can be also set by setPriorProbabilities or withEquiprobableClasses. If equiprobableClasses is set, the probabilities of all classes will be 1/k, where k is classes count.

Nested Class Summary

Nested classes/interfaces inherited from class org.apache.ignite.ml.trainers.DatasetTrainer

DatasetTrainer.EmptyDatasetException

Field Summary

Fields inherited from class org.apache.ignite.ml.trainers.DatasetTrainer

envBuilder, environment

Constructor Summary

Constructors

Constructor and Description
GaussianNaiveBayesTrainer()

Method Summary

Modifier and Type	Method and Description
<K,V> GaussianNaiveBayesModel	fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains model based on the specified data.
boolean	isUpdateable(GaussianNaiveBayesModel mdl)
GaussianNaiveBayesTrainer	resetSettings() Sets default settings.
GaussianNaiveBayesTrainer	setPriorProbabilities(double[] priorProbabilities) Sets prior probabilities.
protected <K,V> GaussianNaiveBayesModel	updateModel(GaussianNaiveBayesModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains new model taken previous one as a first approximation.
GaussianNaiveBayesTrainer	withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
GaussianNaiveBayesTrainer	withEquiprobableClasses() Sets equal probability for all classes.

Methods inherited from class org.apache.ignite.ml.trainers.DatasetTrainer

fit, fit, fit, fit, fit, fit, getLastTrainedModelOrThrowEmptyDatasetException, identityTrainer, learningEnvironment, update, update, update, update, update, withConvertedLabels

Methods inherited from class java.lang.Object

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

Constructor Detail

GaussianNaiveBayesTrainer

public GaussianNaiveBayesTrainer()

Method Detail

fitWithInitializedDeployingContext

public <K,V> GaussianNaiveBayesModel fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder,
                                                                        Preprocessor<K,V> extractor)

Trains model based on the specified data.

Specified by:

fitWithInitializedDeployingContext in class DatasetTrainer<GaussianNaiveBayesModel,Double>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

datasetBuilder - Dataset builder.

extractor - Extractor of UpstreamEntry into LabeledVector.

Returns:

Model.

isUpdateable

public boolean isUpdateable(GaussianNaiveBayesModel mdl)

Specified by:

isUpdateable in class DatasetTrainer<GaussianNaiveBayesModel,Double>

Parameters:

mdl - Model.

Returns:

True if current critical for training parameters correspond to parameters from last training.

withEnvironmentBuilder

public GaussianNaiveBayesTrainer withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)

Changes learning Environment.

Overrides:

withEnvironmentBuilder in class DatasetTrainer<GaussianNaiveBayesModel,Double>

Parameters:

envBuilder - Learning environment builder.

updateModel

protected <K,V> GaussianNaiveBayesModel updateModel(GaussianNaiveBayesModel mdl,
                                                    DatasetBuilder<K,V> datasetBuilder,
                                                    Preprocessor<K,V> extractor)

Trains new model taken previous one as a first approximation.

Specified by:

updateModel in class DatasetTrainer<GaussianNaiveBayesModel,Double>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

mdl - Learned model.

datasetBuilder - Dataset builder.

extractor - Extractor of UpstreamEntry into LabeledVector.

Returns:

Updated model.

withEquiprobableClasses

public GaussianNaiveBayesTrainer withEquiprobableClasses()

Sets equal probability for all classes.

setPriorProbabilities

public GaussianNaiveBayesTrainer setPriorProbabilities(double[] priorProbabilities)

Sets prior probabilities.

resetSettings

public GaussianNaiveBayesTrainer resetSettings()

Sets default settings.