## Uses of Class
org.apache.ignite.ml.tree.randomforest.data.TreeNode

- Packages that use TreeNode
  Package | Description
  --- | ---
  org.apache.ignite.ml.tree.randomforest | Contains random forest implementation classes.
  org.apache.ignite.ml.tree.randomforest.data | Package contains helper data structures for random forest implementation.
  org.apache.ignite.ml.tree.randomforest.data.impurity | Contains implementation of impurity computers based on histograms.

- - ### Uses of TreeNode in org.apache.ignite.ml.tree.randomforest

    Method parameters in org.apache.ignite.ml.tree.randomforest with type arguments of type TreeNode
    Modifier and Type | Method and Description
    --- | ---
    `protected ArrayList<RandomForestTreeModel>` | RandomForestTrainer.`initTrees(Queue<TreeNode> treesQueue)` Creates list of trees.
    `T` | RandomForestTrainer.`withNodesToLearnSelectionStrgy(Function<Queue<TreeNode>,List<TreeNode>> strgy)` Sets strategy for selection nodes from learning queue in each iteration.
    `T` | RandomForestTrainer.`withNodesToLearnSelectionStrgy(Function<Queue<TreeNode>,List<TreeNode>> strgy)` Sets strategy for selection nodes from learning queue in each iteration.

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

    Methods in org.apache.ignite.ml.tree.randomforest.data that return TreeNode
    Modifier and Type | Method and Description
    --- | ---
    `TreeNode` | TreeNode.`getLeft()`
    `TreeNode` | TreeNode.`getRight()`
    `TreeNode` | RandomForestTreeModel.`getRootNode()`

    Methods in org.apache.ignite.ml.tree.randomforest.data that return types with arguments of type TreeNode
    Modifier and Type | Method and Description
    --- | ---
    `List<TreeNode>` | RandomForestTreeModel.`leafs()`
    `List<TreeNode>` | NodeSplit.`split(TreeNode node)` Split node from parameter onto two children nodes.
    `List<TreeNode>` | TreeNode.`toConditional(int featureId, double val)` Convert node to conditional node.

    Methods in org.apache.ignite.ml.tree.randomforest.data with parameters of type TreeNode
    Modifier and Type | Method and Description
    --- | ---
    `void` | NodeSplit.`createLeaf(TreeNode node)` Convert node to leaf.
    `static String` | RandomForestTreeModel.`printTree(TreeNode node, boolean pretty)` Represents DecisionTree as String.
    `List<TreeNode>` | NodeSplit.`split(TreeNode node)` Split node from parameter onto two children nodes.

    Constructors in org.apache.ignite.ml.tree.randomforest.data with parameters of type TreeNode
    Constructor and Description
    `RandomForestTreeModel(TreeNode root, Set<Integer> usedFeatures)` Create an instance of TreeRoot.

  - ### Uses of TreeNode in org.apache.ignite.ml.tree.randomforest.data.impurity

    Method parameters in org.apache.ignite.ml.tree.randomforest.data.impurity with type arguments of type TreeNode
    Modifier and Type | Method and Description
    --- | ---
    `Map<NodeId,ImpurityHistogramsComputer.NodeImpurityHistograms<S>>` | ImpurityHistogramsComputer.`aggregateImpurityStatistics(ArrayList<RandomForestTreeModel> roots, Map<Integer,BucketMeta> histMeta, Map<NodeId,TreeNode> nodesToLearn, Dataset<EmptyContext,BootstrappedDatasetPartition> dataset)` Computes histograms for each feature.

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Release Date | : April 25 2023