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.
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org.apache.ignite.ml.tree.randomforest.data.impurity |
Contains implementation of impurity computers based on histograms.
|
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.
|
Modifier and Type | Method and Description |
---|---|
TreeNode |
TreeNode.getLeft() |
TreeNode |
TreeNode.getRight() |
TreeNode |
RandomForestTreeModel.getRootNode() |
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.
|
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.
|
Constructor and Description |
---|
RandomForestTreeModel(TreeNode root,
Set<Integer> usedFeatures)
Create an instance of TreeRoot.
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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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Ignite Database and Caching Platform : ver. 2.12.0 Release Date : January 10 2022