Efficient Kernel Smoothing Regression using KD-Tree

Version (2.4 KB) by Yi Cao
Efficiency improved multivariant kernel regression using kd-tree
Updated 25 Mar 2008

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Kernel regression is a power full tool for smoothing, image and signal processing, etc. However, it is computationally expensive when it is extented for multivariant cases. The efficiency can be improved by only using neighbors within the effective range arond a regression point. To improve the efficiency further, the kd-tree tool developed by Steven Michael http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=7030&objectType=file is used to efficiently identify points within a range. For large data sets, this code can reduce computation time by 3 to 5 times.

Cite As

Yi Cao (2024). Efficient Kernel Smoothing Regression using KD-Tree (https://www.mathworks.com/matlabcentral/fileexchange/19308-efficient-kernel-smoothing-regression-using-kd-tree), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2007b
Compatible with any release
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