Unsupervised feature selection based on principal components analysis

• المؤلف الرئيسي: Fang, Ji
• مؤلفون آخرون: Mao, Kezhi
• التنسيق: Theses and Dissertations
• منشور في: 2008
• الموضوعات: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• الوصول للمادة أونلاين: http://hdl.handle.net/10356/4238

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—...