Random projection trees are a type of data structure that uses random projections to partition high-dimensional data into a tree format, enabling efficient approximate nearest neighbor search. By applying random projections, the data can be transformed into a lower-dimensional space while preserving distances, which is crucial for handling high-dimensional data in computational geometry. This method allows for faster searching and retrieval processes while maintaining acceptable levels of accuracy.
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