Improving Class Separation in Principal Component Analysis Using Delta Analysis
نویسندگان
چکیده
A method of generating complementary eigenspaces optimised for inter-class and intra-class separability respectively is presented. The objective of creating these spaces is to improve the efficiency of eigenspace search algorithms. The inter-class optimised space may also be used to improve classification and a quantitative evaluation of this against conventional Principal Component Analysis and Canonical analysis (based on Linear Discriminant Analysis) is presented. A qualitative comparison of the intra-class optimised space and spaces produced by Principal Component Analysis on single data classes is also presented.
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تاریخ انتشار 1998