Identification of the hierarchical data structure

  • Authors:

  • I. E. Shepelev

  • Affiliations:

  • Research Institute of Neurocybernetics, Southern Federal University, Rostov-on-Don, Russia 344090

  • Venue:
  • Pattern Recognition and Image Analysis
  • Year:
  • 2011

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Abstract

The task of identifying a hierarchical data structure is considered for the example of the problem of identifying personalizing reference characteristics. A model of a neural network based on radial basis functions is proposed as a possible solution of the task. The identification of the hierarchical dependence is practically aimed to create a classifier using a restricted set of input variables compared to the flat structured classifier. A multilayer perceptron is used as local classifiers. We also use self-organizing maps to visually show data structuredness.