org.apache.ignite.ml.knn.ann

Class ANNClassificationTrainer

java.lang.Object

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

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

org.apache.ignite.ml.knn.ann.ANNClassificationTrainer

public class ANNClassificationTrainer
extends SingleLabelDatasetTrainer<ANNClassificationModel>

ANN algorithm trainer to solve multi-class classification task. This trainer is based on ACD strategy and KMeans clustering algorithm to find centroids.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ANNClassificationTrainer.CentroidStat Service class used for statistics.

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
ANNClassificationTrainer()

Method Summary

Modifier and Type	Method and Description
<K,V> ANNClassificationModel	fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains model based on the specified data.
DistanceMeasure	getDistance() Gets the distance.
double	getEpsilon() Gets the epsilon.
int	getK() Gets the amount of clusters.
int	getMaxIterations() Gets the max number of iterations before convergence.
boolean	isUpdateable(ANNClassificationModel mdl)
protected <K,V> ANNClassificationModel	updateModel(ANNClassificationModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> extractor) Trains new model taken previous one as a first approximation.
ANNClassificationTrainer	withDistance(DistanceMeasure distance) Set up the distance.
ANNClassificationTrainer	withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
ANNClassificationTrainer	withEpsilon(double epsilon) Set up the epsilon.
ANNClassificationTrainer	withK(int k) Set up the amount of clusters.
ANNClassificationTrainer	withMaxIterations(int maxIterations) Set up the max number of iterations before convergence.

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

ANNClassificationTrainer

public ANNClassificationTrainer()

Method Detail

fitWithInitializedDeployingContext

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

Trains model based on the specified data.

Specified by:

fitWithInitializedDeployingContext in class DatasetTrainer<ANNClassificationModel,Double>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

Parameters:

datasetBuilder - Dataset builder.

extractor - Mapping from upstream entry to LabeledVector.

Returns:

Model.

updateModel

protected <K,V> ANNClassificationModel updateModel(ANNClassificationModel 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<ANNClassificationModel,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(ANNClassificationModel mdl)

Specified by:

isUpdateable in class DatasetTrainer<ANNClassificationModel,Double>

Parameters:

mdl - Model.

Returns:

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

withEnvironmentBuilder

public ANNClassificationTrainer withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)

Changes learning Environment.

Overrides:

withEnvironmentBuilder in class DatasetTrainer<ANNClassificationModel,Double>

Parameters:

envBuilder - Learning environment builder.

getK

public int getK()

Gets the amount of clusters.

Returns:

The parameter value.

withK

public ANNClassificationTrainer withK(int k)

Set up the amount of clusters.

Parameters:

k - The parameter value.

Returns:

Model with new amount of clusters parameter value.

getMaxIterations

public int getMaxIterations()

Gets the max number of iterations before convergence.

Returns:

The parameter value.

withMaxIterations

public ANNClassificationTrainer withMaxIterations(int maxIterations)

Set up the max number of iterations before convergence.

Parameters:

maxIterations - The parameter value.

Returns:

Model with new max number of iterations before convergence parameter value.

getEpsilon

public double getEpsilon()

Gets the epsilon.

Returns:

The parameter value.

withEpsilon

public ANNClassificationTrainer withEpsilon(double epsilon)

Set up the epsilon.

Parameters:

epsilon - The parameter value.

Returns:

Model with new epsilon parameter value.

getDistance

public DistanceMeasure getDistance()

Gets the distance.

Returns:

The parameter value.

withDistance

public ANNClassificationTrainer withDistance(DistanceMeasure distance)

Set up the distance.

Parameters:

distance - The parameter value.

Returns:

Model with new distance parameter value.