org.apache.ignite.ml.regressions.linear

Class LinearRegressionLSQRTrainer

java.lang.Object

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

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

org.apache.ignite.ml.regressions.linear.LinearRegressionLSQRTrainer

public class LinearRegressionLSQRTrainer
extends SingleLabelDatasetTrainer<LinearRegressionModel>

Trainer of the linear regression model based on LSQR algorithm.

See Also:

AbstractLSQR

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
LinearRegressionLSQRTrainer()

Method Summary

Modifier and Type	Method and Description
<K,V> LinearRegressionModel	fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains model based on the specified data.
boolean	isUpdateable(LinearRegressionModel mdl)
protected <K,V> LinearRegressionModel	updateModel(LinearRegressionModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains new model taken previous one as a first approximation.

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, withEnvironmentBuilder

Methods inherited from class java.lang.Object

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

Constructor Detail

LinearRegressionLSQRTrainer

public LinearRegressionLSQRTrainer()

Method Detail

fitWithInitializedDeployingContext

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

Trains model based on the specified data.

Specified by:

fitWithInitializedDeployingContext in class DatasetTrainer<LinearRegressionModel,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.

updateModel

protected <K,V> LinearRegressionModel updateModel(LinearRegressionModel 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<LinearRegressionModel,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.

isUpdateable

public boolean isUpdateable(LinearRegressionModel mdl)

Specified by:

isUpdateable in class DatasetTrainer<LinearRegressionModel,Double>

Parameters:

mdl - Model.

Returns:

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