## Uses of Class
org.apache.ignite.ml.tree.data.DecisionTreeData

- Packages that use DecisionTreeData
  Package | Description
  --- | ---
  org.apache.ignite.ml.tree | Root package for decision trees.
  org.apache.ignite.ml.tree.data | Contains data and data builder required for decision tree trainers built on top of partition based dataset.
  org.apache.ignite.ml.tree.impurity | Root package for decision tree impurity measures and calculators.
  org.apache.ignite.ml.tree.impurity.gini | Contains Gini impurity measure and calculator.
  org.apache.ignite.ml.tree.impurity.mse | Contains mean squared error impurity measure and calculator.
  org.apache.ignite.ml.tree.leaf | Root package for decision trees leaf builders.

- - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree

    Method parameters in org.apache.ignite.ml.tree with type arguments of type DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> DecisionTreeModel` | DecisionTreeTrainer.`fit(Dataset<EmptyContext,DecisionTreeData> dataset)`
    `protected ImpurityMeasureCalculator<MSEImpurityMeasure>` | DecisionTreeRegressionTrainer.`getImpurityMeasureCalculator(Dataset<EmptyContext,DecisionTreeData> dataset)` Returns impurity measure calculator.
    `protected abstract ImpurityMeasureCalculator<T>` | DecisionTreeTrainer.`getImpurityMeasureCalculator(Dataset<EmptyContext,DecisionTreeData> dataset)` Returns impurity measure calculator.
    `protected ImpurityMeasureCalculator<GiniImpurityMeasure>` | DecisionTreeClassificationTrainer.`getImpurityMeasureCalculator(Dataset<EmptyContext,DecisionTreeData> dataset)` Returns impurity measure calculator.

  - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree.data

    Methods in org.apache.ignite.ml.tree.data that return DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `DecisionTreeData` | DecisionTreeDataBuilder.`build(LearningEnvironment envBuilder, Iterator<UpstreamEntry<K,V>> upstreamData, long upstreamDataSize, C ctx)` Builds a new partition `data` from a partition `upstream` data and partition `context`.
    `DecisionTreeData` | DecisionTreeData.`filter(TreeFilter filter)` Filters objects and returns only data that passed filter.

  - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree.impurity

    Methods in org.apache.ignite.ml.tree.impurity with parameters of type DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `abstract StepFunction<T>[]` | ImpurityMeasureCalculator.`calculate(DecisionTreeData data, TreeFilter filter, int depth)` Calculates all impurity measures required required to find a best split and returns them as an array of `StepFunction` (for every column).
    `protected int` | ImpurityMeasureCalculator.`columnsCount(DecisionTreeData data, TreeDataIndex idx)` Returns columns count in current dataset.
    `protected double` | ImpurityMeasureCalculator.`getFeatureValue(DecisionTreeData data, TreeDataIndex idx, int featureId, int k)` Returns feature value in according to kth order statistic.
    `protected Vector` | ImpurityMeasureCalculator.`getFeatureValues(DecisionTreeData data, TreeDataIndex idx, int featureId, int k)` Returns feature value in according to kth order statistic.
    `protected double` | ImpurityMeasureCalculator.`getLabelValue(DecisionTreeData data, TreeDataIndex idx, int featureId, int k)` Returns label value in according to kth order statistic.
    `protected int` | ImpurityMeasureCalculator.`rowsCount(DecisionTreeData data, TreeDataIndex idx)` Returns rows count in current dataset.

  - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree.impurity.gini

    Methods in org.apache.ignite.ml.tree.impurity.gini with parameters of type DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `StepFunction<GiniImpurityMeasure>[]` | GiniImpurityMeasureCalculator.`calculate(DecisionTreeData data, TreeFilter filter, int depth)` Calculates all impurity measures required required to find a best split and returns them as an array of `StepFunction` (for every column).

  - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree.impurity.mse

    Methods in org.apache.ignite.ml.tree.impurity.mse with parameters of type DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `StepFunction<MSEImpurityMeasure>[]` | MSEImpurityMeasureCalculator.`calculate(DecisionTreeData data, TreeFilter filter, int depth)` Calculates all impurity measures required required to find a best split and returns them as an array of `StepFunction` (for every column).

  - ### Uses of DecisionTreeData in org.apache.ignite.ml.tree.leaf

    Method parameters in org.apache.ignite.ml.tree.leaf with type arguments of type DecisionTreeData
    Modifier and Type | Method and Description
    --- | ---
    `DecisionTreeLeafNode` | DecisionTreeLeafBuilder.`createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred)` Creates new leaf node for given dataset and node predicate.
    `DecisionTreeLeafNode` | MeanDecisionTreeLeafBuilder.`createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred)` Creates new leaf node for given dataset and node predicate.
    `DecisionTreeLeafNode` | MostCommonDecisionTreeLeafBuilder.`createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred)` Creates new leaf node for given dataset and node predicate.

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Release Date | : April 25 2023