Feature Weighting

版本 1.0.1.4 (4.0 KB) 作者: Dalwinder Singh

MATLAB Source Code for Feature Weighting with Ant Lion optimization

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更新时间 2020/12/13

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In this code Ant Lion optimization is used to search the feature weights along with the optimal value of nearest neighbor parameter (i.e. k) simultaneously.

Run Main.m file for demo.

The feature weighting with ALO is implemented in FW_ALO.m file. Check this file for more details.

The source code and datasets are also available at GitHub: https://github.com/dalwindercheema/featweight

引用格式

Singh, Dalwinder, and Birmohan Singh. “Hybridization of Feature Selection and Feature Weighting for High Dimensional Data.” Applied Intelligence, vol. 49, no. 4, Springer Science and Business Media LLC, Nov. 2018, pp. 1580–96, doi:10.1007/s10489-018-1348-2.

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创建方式 R2019b

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MATLAB > Mathematics > Graph and Network Algorithms > Shortest Path > Traveling Salesman (TSP) >

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参考作品: Ant Lion Optimizer (ALO)

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版本	已发布	发行说明
1.0.1.4	2020/12/13	Minor Change in Code	下载
1.0.1.3	2020/2/9	Description Update	下载
1.0.1.2	2020/2/9	Description Update	下载
1.0.1.1	2020/1/5	Description Update	下载
1.0.1	2020/1/4	Description updated	下载
1.0.0	2020/1/3		下载

MLA	Singh, Dalwinder, and Birmohan Singh. “Hybridization of Feature Selection and Feature Weighting for High Dimensional Data.” Applied Intelligence, vol. 49, no. 4, Springer Science and Business Media LLC, Nov. 2018, pp. 1580–96, doi:10.1007/s10489-018-1348-2.
APA	Singh, D., & Singh, B. (2018). Hybridization of feature selection and feature weighting for high dimensional data. Applied Intelligence, 49(4), 1580–1596. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs10489-018-1348-2
BibTeX	@article{Singh_2018, doi = {10.1007/s10489-018-1348-2}, url = {https://doi.org/10.1007%2Fs10489-018-1348-2}, year = 2018, month = {nov}, publisher = {Springer Science and Business Media {LLC}}, volume = {49}, number = {4}, pages = {1580--1596}, author = {Dalwinder Singh and Birmohan Singh}, title = {Hybridization of feature selection and feature weighting for high dimensional data}, journal = {Applied Intelligence} }