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...

Full description

Bibliographic Details
Published in:Knowledge and Information Systems
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
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

Internet

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176106868&doi=10.1007%2fs10115-023-01993-5&partnerID=40&md5=7625ea19a71f40771238c85b88344422

Similar Items