Supervised feature selection using principal component analysis

Supervised feature selection using principal component analysis

The principal component analysis (PCA) is widely used in computational science branches such as computer science, pattern recognition, and machine learning, as it can effectively reduce the dimensionality of high-dimensional data. In particular, it is a popular transformation method used for feature...

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Bibliographic Details
Main Authors: Rahmat, Fariq, Zulkafli, Zed, Ishak, Asnor Juraiza, Abdul Rahman, Ribhan Zafira, Stercke, Simon De, Buytaert, Wouter, Tahir, Wardah, Ab Rahman, Jamalludin, Ibrahim, Salwa, Ismail, Muhamad
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2023
Online Access:http://psasir.upm.edu.my/id/eprint/110338/
https://link.springer.com/article/10.1007/s10115-023-01993-5?error=cookies_not_supported&code=26d4082c-44cd-4a6b-95c7-0d84a3dabd51
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Institution: Universiti Putra Malaysia

Internet

http://psasir.upm.edu.my/id/eprint/110338/
https://link.springer.com/article/10.1007/s10115-023-01993-5?error=cookies_not_supported&code=26d4082c-44cd-4a6b-95c7-0d84a3dabd51

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