Unsupervised feature selection based on principal components analysis

• Main Author: Fang, Ji
• Other Authors: Mao, Kezhi
• Format: Theses and Dissertations
• Published: 2008
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: http://hdl.handle.net/10356/4238
• Institution: Nanyang Technological University

An important issue related to mining large data sets, both in dimension and size, is of selecting a subset of the original features. In this thesis, we describe an unsupervised feature selection algorithm suitable for data sets, large in both dimension and size. The algorithm consists of two steps—...