Supervised feature selection using principal component analysis

• 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

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...