Fast orthogonal forward selection algorithm for feature subset selection
Tóm tắt
Feature selection is an important issue in pattern classification. In the presented study, we develop a fast orthogonal forward selection (FOFS) algorithm for feature subset selection. The FOFS algorithm employs an orthogonal transform to decompose correlations among candidate features, but it performs the orthogonal decomposition in an implicit way. Consequently, the fast algorithm demands less computational effort as compared with conventional orthogonal forward selection (OFS).
Từ khóa
#Feature extraction #Filters #Search methods #Parameter estimation #Multi-layer neural network #Training data #Extraterrestrial measurements #Classification algorithms #Neural networks #Pattern classificationTài liệu tham khảo
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