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Cluster analysis based on dimensional information with applications to feature selection and classification (1974)

Northouse, R. A. ; Eigen, D. J. ; Fromm, F. R.

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Publication Date: 2019-06-27

Description: A new clustering algorithm is presented that is based on dimensional information. The algorithm includes an inherent feature selection criterion, which is discussed. Further, a heuristic method for choosing the proper number of intervals for a frequency distribution histogram, a feature necessary for the algorithm, is presented. The algorithm, although usable as a stand-alone clustering technique, is then utilized as a global approximator. Local clustering techniques and configuration of a global-local scheme are discussed, and finally the complete global-local and feature selector configuration is shown in application to a real-time adaptive classification scheme for the analysis of remote sensed multispectral scanner data.

Keywords: COMPUTERS

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