## 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.

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