Intel® oneAPI Data Analytics Library Developer Guide and Reference
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k-d Tree
k-d tree is a space-partitioning binary tree [Bentley80], where
Each non-leaf node induces the hyperplane that splits the feature space into two parts. To define the splitting hyperplane explicitly, a non-leaf node stores the identifier of the feature (that defines axis in the feature space) and a cut-point
Each leaf node of the tree has an associated subset (a bucket) of elements of the training data set. Feature vectors from a bucket belong to the region of the space defined by tree nodes on the path from the root node to the respective leaf.
Related terms
- A cut-point
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A feature value that corresponds to a non-leaf node of a k-d tree and defines the splitting hyperplane orthogonal to the axis specified by the given feature.