A Comparative Study of Catalogue-Based Classification
In this paper we study the performance of a catalogue-based image classifier after applying different methods for performance improvement, such as feature-subset selection and feature weighting. The performance of the image catalogues is assessed by studying the reduction of the prototypes after applying Chang‘s prototype-selection algorithm. We describe the results that could be achieved and give an outlook for further developments on a catalogue-based classifier.
KeywordsClassification Accuracy Gray Level Feature Subset Respiratory Sinus Arrhythmia Decision Tree Induction
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