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

- Packages that use DecisionTreeNode
  Package | Description
  --- | ---
  org.apache.ignite.ml.tree | Root package for decision trees.
  org.apache.ignite.ml.xgboost | Base package for XGBoost model parser, correspondent DTOs and util classes.
  org.apache.ignite.ml.xgboost.parser.visitor | Base package for XGBoost model parser ANTLR visitor.

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

    Classes in org.apache.ignite.ml.tree that implement DecisionTreeNode
    Modifier and Type | Class and Description
    --- | ---
    `class` | `DecisionTreeConditionalNode` Decision tree conditional (non-leaf) node.
    `class` | `DecisionTreeLeafNode` Decision tree leaf node which contains value.

    Methods in org.apache.ignite.ml.tree that return DecisionTreeNode
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> DecisionTreeNode` | DecisionTree.`fit(Dataset<EmptyContext,DecisionTreeData> dataset)`
    `<K,V> DecisionTreeNode` | DecisionTree.`fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Trains model based on the specified data.
    `DecisionTreeNode` | DecisionTreeConditionalNode.`getElseNode()`
    `DecisionTreeNode` | DecisionTreeConditionalNode.`getMissingNode()`
    `DecisionTreeNode` | DecisionTreeConditionalNode.`getThenNode()`
    `protected <K,V> DecisionTreeNode` | DecisionTree.`updateModel(DecisionTreeNode mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Trains new model based on dataset because there is no valid approach to update decision trees.

    Methods in org.apache.ignite.ml.tree with parameters of type DecisionTreeNode
    Modifier and Type | Method and Description
    --- | ---
    `boolean` | DecisionTree.`isUpdateable(DecisionTreeNode mdl)`
    `static String` | DecisionTree.`printTree(DecisionTreeNode node, boolean pretty)` Represents DecisionTree as String.
    `void` | DecisionTreeConditionalNode.`setElseNode(DecisionTreeNode elseNode)`
    `void` | DecisionTreeConditionalNode.`setMissingNode(DecisionTreeNode missingNode)`
    `void` | DecisionTreeConditionalNode.`setThenNode(DecisionTreeNode thenNode)`
    `protected <K,V> DecisionTreeNode` | DecisionTree.`updateModel(DecisionTreeNode mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Trains new model based on dataset because there is no valid approach to update decision trees.

    Constructors in org.apache.ignite.ml.tree with parameters of type DecisionTreeNode
    Constructor and Description
    `DecisionTreeConditionalNode(int col, double threshold, DecisionTreeNode thenNode, DecisionTreeNode elseNode, DecisionTreeNode missingNode)` Constructs a new instance of decision tree conditional node.

  - ### Uses of DecisionTreeNode in org.apache.ignite.ml.xgboost

    Constructor parameters in org.apache.ignite.ml.xgboost with type arguments of type DecisionTreeNode
    Constructor and Description
    `XGModelComposition(Map<String,Integer> dict, List<DecisionTreeNode> models)` Constructs a new instance of composition of models.

  - ### Uses of DecisionTreeNode in org.apache.ignite.ml.xgboost.parser.visitor

    Methods in org.apache.ignite.ml.xgboost.parser.visitor that return DecisionTreeNode
    Modifier and Type | Method and Description
    --- | ---
    `DecisionTreeNode` | XGTreeVisitor.`visitXgTree(XGBoostModelParser.XgTreeContext ctx)` Visit a parse tree produced by `XGBoostModelParser.xgTree()`.

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Release Date | : October 15 2020