Abstract
In this paper we describe a method of advanced data preprocessing for pattern classification using a fuzzy classification system (FCS). Input pattern vectors are transformed using a matrix before classification to improve classification results and to simplify the FCS. The transformation matrix is calculated using the prototypes obtained with fuzzy clustering methods. The data preprocessed in this way are often classifiable more easily than the original data. Results obtained with the new method using artificially created data and the well-known Iris data set are presented.
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