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Efficient Kernel Smoothing Regression using KD-Tree 1.0

  Date Added: April 18, 2013  |  Visits: 179

Efficient Kernel Smoothing Regression using KD-Tree

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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/fil...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.

Requirements: No special requirements
Platforms: Matlab
Keyword: Arond Developed Improve Kdtree Michael Point Range Reduce Steven
Users rating: 0/10

License: Shareware Size: 10 KB
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