## Uses of Interface
org.apache.ignite.ml.tree.TreeFilter

- Packages that use TreeFilter
  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 TreeFilter in org.apache.ignite.ml.tree

    Methods in org.apache.ignite.ml.tree that return TreeFilter
    Modifier and Type | Method and Description
    --- | ---
    `default TreeFilter` | TreeFilter.`and(TreeFilter other)` Returns a composed predicate.

    Methods in org.apache.ignite.ml.tree with parameters of type TreeFilter
    Modifier and Type | Method and Description
    --- | ---
    `default TreeFilter` | TreeFilter.`and(TreeFilter other)` Returns a composed predicate.

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

    Methods in org.apache.ignite.ml.tree.data with parameters of type TreeFilter
    Modifier and Type | Method and Description
    --- | ---
    `TreeDataIndex` | DecisionTreeData.`createIndexByFilter(int depth, TreeFilter filter)` Builds index in according to current tree depth and cached indexes in upper levels.
    `TreeDataIndex` | TreeDataIndex.`filter(TreeFilter filter)` Creates projection of current index in according to `TreeFilter`.
    `DecisionTreeData` | DecisionTreeData.`filter(TreeFilter filter)` Filters objects and returns only data that passed filter.

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

    Methods in org.apache.ignite.ml.tree.impurity with parameters of type TreeFilter
    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).

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

    Methods in org.apache.ignite.ml.tree.impurity.gini with parameters of type TreeFilter
    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 TreeFilter in org.apache.ignite.ml.tree.impurity.mse

    Methods in org.apache.ignite.ml.tree.impurity.mse with parameters of type TreeFilter
    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 TreeFilter in org.apache.ignite.ml.tree.leaf

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

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Release Date | : December 9 2020