Online Dynamic Value System for Machine Learning

Authors:
Haibo He;Janusz A. Starzyk
Affiliations:
Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA;School of Electrical Engineering and Computer Science, Ohio University, Athens, OH 45701, USA
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

A novel online dynamic value system for machine learning is proposed in this paper. The proposed system has a dual network structure: data processing network (DPN) and information evaluation network (IEN). The DPN is responsible for numerical data processing, including input space transformation and online dynamic data fitting. The IEN evaluates results provided by DPN. A dynamic three-curve fitting (TCF) scheme provides statistical bounds to the curve fitting according to data distribution. The system uses a shift register communication channel. Application of the proposed value system to the financial analysis (bank prime loan rate prediction) is used to illustrate the effectiveness of the proposed system.