Classification by Density Intersection

Authors:
Yoram Baram
Affiliations:
Computer Science Department, Technion, Israel Institute of Technology, Haifa 32000, Israel E-mail: ybaram@grade.arc.nasa.gor
Venue:
Neural Processing Letters
Year:
1998

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Abstract

A classification method based on the intersection surface between twoparameterized densities is proposed. The densities are obtained fromclass-labeled data by maximizing the mutual information across a system of integrated Gaussians, but, in practice, only theintersection surface needs to be estimated. The application of theproposed technique is demonstrated by predicting stock behavior.