Uses of Class
org.apache.ignite.ml.dataset.impl.bootstrapping.BootstrappedVector

Packages that use BootstrappedVector

Package	Description
org.apache.ignite.ml.dataset.impl.bootstrapping	Base package for bootstrapped implementation of machine learning dataset.
org.apache.ignite.ml.tree.randomforest	Contains random forest implementation classes.
org.apache.ignite.ml.tree.randomforest.data.impurity	Contains implementation of impurity computers based on histograms.
org.apache.ignite.ml.tree.randomforest.data.impurity.basic	Contains implementation of basic classes for impurity computers.
org.apache.ignite.ml.tree.randomforest.data.statistics	Contains implementation of statistics computers for Random Forest.

Uses of BootstrappedVector in org.apache.ignite.ml.dataset.impl.bootstrapping

Methods in org.apache.ignite.ml.dataset.impl.bootstrapping that return BootstrappedVector

Modifier and Type	Method and Description
BootstrappedVector	BootstrappedDatasetPartition.getRow(int rowId) Returns vector from dataset in according to row id.

Constructors in org.apache.ignite.ml.dataset.impl.bootstrapping with parameters of type BootstrappedVector

Constructor and Description
BootstrappedDatasetPartition(BootstrappedVector[] vectors) Creates an instance of BootstrappedDatasetPartition.

Uses of BootstrappedVector in org.apache.ignite.ml.tree.randomforest

Classes in org.apache.ignite.ml.tree.randomforest with type parameters of type BootstrappedVector

Modifier and Type	Class and Description
class	RandomForestTrainer<L,S extends ImpurityComputer<BootstrappedVector,S>,T extends RandomForestTrainer<L,S,T>> Class represents a realization of Random Forest algorithm.

Methods in org.apache.ignite.ml.tree.randomforest that return types with arguments of type BootstrappedVector

Modifier and Type	Method and Description
protected LeafValuesComputer<ObjectHistogram<BootstrappedVector>>	RandomForestClassifierTrainer.createLeafStatisticsAggregator() Creates an instance of Leaf Statistics Aggregator corresponding to RF implementation.

Uses of BootstrappedVector in org.apache.ignite.ml.tree.randomforest.data.impurity

Classes in org.apache.ignite.ml.tree.randomforest.data.impurity with type parameters of type BootstrappedVector

Modifier and Type	Class and Description
class	ImpurityHistogramsComputer<S extends ImpurityComputer<BootstrappedVector,S>> Class containing logic of aggregation impurity statistics within learning dataset.
static class	ImpurityHistogramsComputer.NodeImpurityHistograms<S extends ImpurityComputer<BootstrappedVector,S>> Class represents per feature statistics for impurity computing.

Methods in org.apache.ignite.ml.tree.randomforest.data.impurity with parameters of type BootstrappedVector

Modifier and Type	Method and Description
void	MSEHistogram.addElement(BootstrappedVector vector) Add object to histogram.
void	GiniHistogram.addElement(BootstrappedVector vector) Add object to histogram.

Uses of BootstrappedVector in org.apache.ignite.ml.tree.randomforest.data.impurity.basic

Methods in org.apache.ignite.ml.tree.randomforest.data.impurity.basic that return types with arguments of type BootstrappedVector

Modifier and Type	Method and Description
ObjectHistogram<BootstrappedVector>	CountersHistogram.newInstance() Creates an instance of ObjectHistogram from child class.

Methods in org.apache.ignite.ml.tree.randomforest.data.impurity.basic with parameters of type BootstrappedVector

Modifier and Type	Method and Description
Integer	BootstrappedVectorsHistogram.mapToBucket(BootstrappedVector vec) Bucket mapping.
Double	CountersHistogram.mapToCounter(BootstrappedVector vec) Counter mapping.

Uses of BootstrappedVector in org.apache.ignite.ml.tree.randomforest.data.statistics

Methods in org.apache.ignite.ml.tree.randomforest.data.statistics that return types with arguments of type BootstrappedVector

Modifier and Type	Method and Description
protected ObjectHistogram<BootstrappedVector>	ClassifierLeafValuesComputer.createLeafStatsAggregator(int sampleId) Creates an instance of leaf statistics aggregator in according to concrete algorithm based on RandomForest.
protected ObjectHistogram<BootstrappedVector>	ClassifierLeafValuesComputer.mergeLeafStats(ObjectHistogram<BootstrappedVector> leftStats, ObjectHistogram<BootstrappedVector> rightStats) Merge statistics for same leafs.

Methods in org.apache.ignite.ml.tree.randomforest.data.statistics with parameters of type BootstrappedVector

Modifier and Type	Method and Description
protected void	RegressionLeafValuesComputer.addElementToLeafStatistic(MeanValueStatistic leafStatAggr, BootstrappedVector vec, int sampleId) Save vector to leaf statistic.
protected void	ClassifierLeafValuesComputer.addElementToLeafStatistic(ObjectHistogram<BootstrappedVector> leafStatAggr, BootstrappedVector vec, int sampleId) Save vector to leaf statistic.
protected abstract void	LeafValuesComputer.addElementToLeafStatistic(T leafStatAggr, BootstrappedVector vec, int sampleId) Save vector to leaf statistic.

Method parameters in org.apache.ignite.ml.tree.randomforest.data.statistics with type arguments of type BootstrappedVector

Modifier and Type	Method and Description
protected void	ClassifierLeafValuesComputer.addElementToLeafStatistic(ObjectHistogram<BootstrappedVector> leafStatAggr, BootstrappedVector vec, int sampleId) Save vector to leaf statistic.
protected double	ClassifierLeafValuesComputer.computeLeafValue(ObjectHistogram<BootstrappedVector> stat) Returns the most frequent value in according to statistic.
protected ObjectHistogram<BootstrappedVector>	ClassifierLeafValuesComputer.mergeLeafStats(ObjectHistogram<BootstrappedVector> leftStats, ObjectHistogram<BootstrappedVector> rightStats) Merge statistics for same leafs.
protected ObjectHistogram<BootstrappedVector>	ClassifierLeafValuesComputer.mergeLeafStats(ObjectHistogram<BootstrappedVector> leftStats, ObjectHistogram<BootstrappedVector> rightStats) Merge statistics for same leafs.