Generalized inverse approach to clustering, feature selecting, and classification
William G. Wee · IEEE Transactions on Information Theory · 1971
This paper gives a unified approach to designing a data analyzer that performs cluster-seeking, feature selection, and categorizer design under a weighted least-square performance criterion. The cost of misrecognitions is preserved throughout the process, It can be used as a fast procedure to evaluate the discriminatory capability of sensors and/or preprocessors.