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This implements a KDTree for nearest neighbor and range searching.The KDTree stores a N-dimensional set of points. The tree can be queried for all points within a Euclidian range in order O(sqrt(p)+k) time, where p is the number of points and k is the number of reported points. A nearest neighbor search can be done in order O(log(p) time. The m-files are binary MATLAB functions written in C++. Source code is included as well as binaries for Linux on i386 and x86_64 systems and Windows (i386).
Citation pour cette source
Steven Michael (2026). KD Tree Nearest Neighbor and Range Search (https://fr.mathworks.com/matlabcentral/fileexchange/7030-kd-tree-nearest-neighbor-and-range-search), MATLAB Central File Exchange. Extrait(e) le .
Remerciements
A inspiré : Efficient Kernel Smoothing Regression using KD-Tree, Efficient K-Nearest Neighbor Search using JIT, ataiya/kdtree, Kdtree implementation in matlab
Catégories
En savoir plus sur Statistics and Machine Learning Toolbox dans Help Center et MATLAB Answers
Informations générales
- Version 1.0.0.0 (212 ko)
Compatibilité avec les versions de MATLAB
- Compatible avec toutes les versions
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | Action |
|---|---|---|---|
| 1.0.0.0 | Update to compile with MATLAB R2008a. Change to makefile-based Visual Studio solution for windows. |
