An informational energy LVQ approach for feature ranking
نویسندگان
چکیده
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a weighted LVQ algorithm, called Energy Relevance LVQ (ERLVQ), based on Onicescu’s informational energy [10]. ERLVQ is an incremental learning algorithm for supervised classification and feature ranking.
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