A Modal Symbolic Classifier for Interval Data

  • Fabio C. D. Silva
  • Francisco de A.T. de Carvalho
  • Renata M. C. R. de Souza
  • Joyce Q. Silva
Conference paper

DOI: 10.1007/11893257_6

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)
Cite this paper as:
Silva F.C.D., de A.T. de Carvalho F., de Souza R.M.C.R., Silva J.Q. (2006) A Modal Symbolic Classifier for Interval Data. In: King I., Wang J., Chan LW., Wang D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg

Abstract

A modal symbolic classifier for interval data is presented. The proposed method needs a previous pre-processing step to transform interval symbolic data into modal symbolic data. The presented classifier has then as input a set of vectors of weights. In the learning step, each group is also described by a vector of weight distributions obtained through a generalization tool. The allocation step uses the squared Euclidean distance to compare two modal descriptions. To show the usefulness of this method, examples with synthetic symbolic data sets are considered.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fabio C. D. Silva
    • 1
  • Francisco de A.T. de Carvalho
    • 1
  • Renata M. C. R. de Souza
    • 1
  • Joyce Q. Silva
    • 1
  1. 1.Centro de Informatica – CIn / UFPERecifeBrasil

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