Data reduction: feature aggregation

Authors:
Hiroshi Motoda;Huan Liu
Affiliations:
Professor of Intelligent Systems Science, The Institute of Scientific and Industrial Research, Osaka University, Japan;Associate Professor of Computer Science and Engineering, Arizona State University, Tempe
Venue:
Handbook of data mining and knowledge discovery
Year:
2002

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AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1

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Abstract

Feature aggregation is a process through which a set of new features is created, its purpose is improving performance such as estimated accuracy, visualization, and comprehensibility of learned knowledge. Feature aggregation is briefly reviewed in the framework of constructive induction and functional mapping. In the former we introduce basic operators for constructing new features and a typical algorithm; in the latter, we introduce some statistical methods and a neural network method.