org.apache.ignite.ml.svm

Class SVMLinearMultiClassClassificationTrainer

java.lang.Object

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

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

org.apache.ignite.ml.svm.SVMLinearMultiClassClassificationTrainer

public class SVMLinearMultiClassClassificationTrainer
extends SingleLabelDatasetTrainer<SVMLinearMultiClassClassificationModel>

Base class for a soft-margin SVM linear multiclass-classification trainer based on the communication-efficient distributed dual coordinate ascent algorithm (CoCoA) with hinge-loss function. All common parameters are shared with bunch of binary classification trainers.

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

environment

Constructor Summary

Constructors

Constructor and Description
SVMLinearMultiClassClassificationTrainer()

Method Summary

Modifier and Type	Method and Description
protected boolean	checkState(SVMLinearMultiClassClassificationModel mdl)
<K,V> SVMLinearMultiClassClassificationModel	fit(DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Trains model based on the specified data.
int	getAmountOfIterations() Gets the amount of outer iterations of SCDA algorithm.
int	getAmountOfLocIterations() Gets the amount of local iterations of SCDA algorithm.
double	getLambda() Get the regularization lambda.
long	getSeed() Gets the seed number.
<K,V> SVMLinearMultiClassClassificationModel	updateModel(SVMLinearMultiClassClassificationModel mdl, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Gets state of model in arguments, update in according to new data and return new model.
SVMLinearMultiClassClassificationTrainer	withAmountOfIterations(int amountOfIterations) Set up the amount of outer iterations of SCDA algorithm.
SVMLinearMultiClassClassificationTrainer	withAmountOfLocIterations(int amountOfLocIterations) Set up the amount of local iterations of SCDA algorithm.
SVMLinearMultiClassClassificationTrainer	withLambda(double lambda) Set up the regularization parameter.
SVMLinearMultiClassClassificationTrainer	withSeed(long seed) Set up the seed.

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

fit, fit, fit, fit, getLastTrainedModelOrThrowEmptyDatasetException, setEnvironment, update, update, update, update, update

Methods inherited from class java.lang.Object

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

Constructor Detail

SVMLinearMultiClassClassificationTrainer

public SVMLinearMultiClassClassificationTrainer()

Method Detail

fit

public <K,V> SVMLinearMultiClassClassificationModel fit(DatasetBuilder<K,V> datasetBuilder,
                                                        IgniteBiFunction<K,V,Vector> featureExtractor,
                                                        IgniteBiFunction<K,V,Double> lbExtractor)

Trains model based on the specified data.

Specified by:

fit in class DatasetTrainer<SVMLinearMultiClassClassificationModel,Double>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

datasetBuilder - Dataset builder.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Model.

updateModel

public <K,V> SVMLinearMultiClassClassificationModel updateModel(SVMLinearMultiClassClassificationModel mdl,
                                                                DatasetBuilder<K,V> datasetBuilder,
                                                                IgniteBiFunction<K,V,Vector> featureExtractor,
                                                                IgniteBiFunction<K,V,Double> lbExtractor)

Gets state of model in arguments, update in according to new data and return new model.

Specified by:

updateModel in class DatasetTrainer<SVMLinearMultiClassClassificationModel,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.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Returns:

Updated model.

checkState

protected boolean checkState(SVMLinearMultiClassClassificationModel mdl)

Specified by:

checkState in class DatasetTrainer<SVMLinearMultiClassClassificationModel,Double>

Parameters:

mdl - Model.

Returns:

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

withLambda

public SVMLinearMultiClassClassificationTrainer withLambda(double lambda)

Set up the regularization parameter.

Parameters:

lambda - The regularization parameter. Should be more than 0.0.

Returns:

Trainer with new lambda parameter value.

getLambda

public double getLambda()

Get the regularization lambda.

Returns:

The property value.

getAmountOfIterations

public int getAmountOfIterations()

Gets the amount of outer iterations of SCDA algorithm.

Returns:

The property value.

withAmountOfIterations

public SVMLinearMultiClassClassificationTrainer withAmountOfIterations(int amountOfIterations)

Set up the amount of outer iterations of SCDA algorithm.

Parameters:

amountOfIterations - The parameter value.

Returns:

Trainer with new amountOfIterations parameter value.

getAmountOfLocIterations

public int getAmountOfLocIterations()

Gets the amount of local iterations of SCDA algorithm.

Returns:

The property value.

withAmountOfLocIterations

public SVMLinearMultiClassClassificationTrainer withAmountOfLocIterations(int amountOfLocIterations)

Set up the amount of local iterations of SCDA algorithm.

Parameters:

amountOfLocIterations - The parameter value.

Returns:

Trainer with new amountOfLocIterations parameter value.

getSeed

public long getSeed()

Gets the seed number.

Returns:

The property value.

withSeed

public SVMLinearMultiClassClassificationTrainer withSeed(long seed)

Set up the seed.

Parameters:

seed - The parameter value.

Returns:

Model with new seed parameter value.