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Classification by Density Intersection

Abstract

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

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Baram, Y. Classification by Density Intersection. Neural Processing Letters 8, 1–8 (1998). https://doi.org/10.1023/A:1009611427303

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  • DOI: https://doi.org/10.1023/A:1009611427303

Keywords

  • Neural Network
  • Artificial Intelligence
  • Complex System
  • Nonlinear Dynamics
  • Mutual Information