AI engineering glossary · Classical ML algorithms
What is KD-tree?
KD-tree: A tree that repeatedly splits space along one coordinate axis at a time so that nearby points can be found without checking every stored point. It speeds up neighbour search in low to moderate dimensions but loses its advantage as dimensions grow.
KD-tree: an example
Finding the 5 closest of 1 million 3-D points takes roughly logarithmic time using this tree rather than a full scan.
Related terms
- k-nearest neighbours
- Ball tree
- Approximate nearest neighbour
More Classical ML algorithms terms
- Kernel PCA
- Kernel trick
- Laplace smoothing
- Lasso regression
- Lazy learning
- Lift
- LightGBM
- Linear discriminant analysis
Where you learn it
KD-tree is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.