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Impact of Weight Initialization on Multilayer Perceptron Using Fuzzy Similarity Quality Measure

  • Lenniet CoelloEmail author
  • Yumilka Fernández
  • Yaima Filiberto
  • Rafael Bello
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 657)

Abstract

This paper presents an algorithm for initializing the weights in multilayer perceptrons based on the new metrics called Fuzzy Similarity Quality. The new metric used a binary fuzzy relation for quantify the strength of the similarity between two objects. This measure computes the grade of similarity in a decision system in which the features can have discrete or continuous values. Experimental results show that the proposed initialization method performs better than other previously reported methods to calculate the weight of features.

Keywords

Fuzzy Similarity Quality Measure Multilayer perceptrons Weight of features 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Lenniet Coello
    • 1
    Email author
  • Yumilka Fernández
    • 1
  • Yaima Filiberto
    • 1
  • Rafael Bello
    • 2
  1. 1.Department of Computer ScienceUniversidad de CamagüeyCamagüeyCuba
  2. 2.Department of Computer ScienceUniversidad Central de Las VillasSanta ClaraCuba

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