An informational energy LVQ approach for feature ranking

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.

• Type: Conference
• Year: 2004
• Where: ESANN
• Authors: Razvan Andonie, Angel Cataron
• Keywords: ESANN 2004, ESANN 2007, Feature Ranking, Input Feature Ranking, Necessary Preprocessing Stage