org.apache.ignite.ml.composition.boosting.convergence.simple

Class ConvergenceCheckerStub<K,V>

java.lang.Object

org.apache.ignite.ml.composition.boosting.convergence.ConvergenceChecker<K,V>

org.apache.ignite.ml.composition.boosting.convergence.simple.ConvergenceCheckerStub<K,V>

Type Parameters:

K - Type of a key in upstream data.

V - Type of a value in upstream data.

All Implemented Interfaces:

Serializable

public class ConvergenceCheckerStub<K,V>
extends ConvergenceChecker<K,V>

This strategy skip estimating error on dataset step. According to this strategy, training will stop after reaching the maximum number of iterations.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ConvergenceCheckerStub(long sampleSize, IgniteFunction<Double,Double> externalLbToInternalMapping, Loss loss, DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,Vector> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Creates an intance of ConvergenceCheckerStub.

Method Summary

Modifier and Type	Method and Description
Double	computeMeanErrorOnDataset(Dataset<EmptyContext,? extends FeatureMatrixWithLabelsOnHeapData> dataset, ModelsComposition mdl) Compute error for given model on learning dataset.
boolean	isConverged(Dataset<EmptyContext,? extends FeatureMatrixWithLabelsOnHeapData> dataset, ModelsComposition currMdl) Checks convergency on dataset.
boolean	isConverged(DatasetBuilder<K,V> datasetBuilder, ModelsComposition currMdl) Checks convergency on dataset.

Methods inherited from class org.apache.ignite.ml.composition.boosting.convergence.ConvergenceChecker

computeError

Methods inherited from class java.lang.Object

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

Constructor Detail

ConvergenceCheckerStub

public ConvergenceCheckerStub(long sampleSize,
                              IgniteFunction<Double,Double> externalLbToInternalMapping,
                              Loss loss,
                              DatasetBuilder<K,V> datasetBuilder,
                              IgniteBiFunction<K,V,Vector> featureExtractor,
                              IgniteBiFunction<K,V,Double> lbExtractor)

Creates an intance of ConvergenceCheckerStub.

Parameters:

sampleSize - Sample size.

externalLbToInternalMapping - External label to internal mapping.

loss - Loss function.

datasetBuilder - Dataset builder.

featureExtractor - Feature extractor.

lbExtractor - Label extractor.

Method Detail

isConverged

public boolean isConverged(DatasetBuilder<K,V> datasetBuilder,
                           ModelsComposition currMdl)

Checks convergency on dataset.

Overrides:

isConverged in class ConvergenceChecker<K,V>

currMdl - Current model.

Returns:

true if GDB is converged.

isConverged

public boolean isConverged(Dataset<EmptyContext,? extends FeatureMatrixWithLabelsOnHeapData> dataset,
                           ModelsComposition currMdl)

Checks convergency on dataset.

Overrides:

isConverged in class ConvergenceChecker<K,V>

Parameters:

dataset - Dataset.

currMdl - Current model.

Returns:

true if GDB is converged.

computeMeanErrorOnDataset

public Double computeMeanErrorOnDataset(Dataset<EmptyContext,? extends FeatureMatrixWithLabelsOnHeapData> dataset,
                                        ModelsComposition mdl)

Compute error for given model on learning dataset.

Specified by:

computeMeanErrorOnDataset in class ConvergenceChecker<K,V>

Parameters:

dataset - Learning dataset.

mdl - Model.

Returns:

error mean value.