Description: This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing.
The code was initially implemented through vectorization. After discussions with John D Errico, I realized that my algorithm will suffer numerical accurancy problem for data with large values. Then, after trying several approaches, I found simple loops with JIT acceleration is the most efficient solution. Now, the performance of the code is comparable with kd-tree even the latter is coded in a mex file.
The code is very simple, hence is also suitable for beginner to learn knn search.
- [ClusteringToolbox] - This is a cluster box can be used as dat
- [MLkNN] - Data Mining in the area of an algorithm-
- [images] - matlab image processing algorithms, incl
- [knnsearch] - KNN classifiers, training is training s
- [get_NH] - Nearest neighbor clustering algorithm
- [Classifier_NN_f] - Nearest neighbor classifier, matlab envi
File list (Check if you may need any files):
knnsearch.m
license.txt
readme.txt
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