Fast and exact fixed-radius neighbor search based on sorting

Fast and exact fixed-radius neighbor search based on sorting

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Fixed-radius near neighbor search is a fundamental data operation that retrieves all data points within a user-specified distance to a query point.There are efficient algorithms that can provide fast approximate query responses, but they often have a very compute-intensive indexing phase and require careful parameter tuning.Therefore, exact brute force Leg Wraps and tree-based search methods are still widely used.Here we propose a new fixed-radius near neighbor search method, called SNN, that significantly improves over brute force and tree-based methods in terms of index and query time, provably returns exact results, and requires no parameter tuning.SNN exploits a sorting of the data points by their first principal component to prune the query search space.

Further speedup is gained from an efficient implementation using high-level basic linear algebra subprograms (BLAS).We provide theoretical analysis of our method and demonstrate its practical performance Me Christmas Pajama when used stand-alone and when applied within the DBSCAN clustering algorithm.