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...
Published in: | Knowledge and Information Systems |
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Main Author: | Rahmat F.; Zulkafli Z.; Ishak A.J.; Abdul Rahman R.Z.; Stercke S.D.; Buytaert W.; Tahir W.; Ab Rahman J.; Ibrahim S.; Ismail M. |
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media Deutschland GmbH
2024
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176106868&doi=10.1007%2fs10115-023-01993-5&partnerID=40&md5=7625ea19a71f40771238c85b88344422 |
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