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Fuzzy Random Forest with C–Fuzzy Decision Trees

  • Łukasz GadomerEmail author
  • Zenon A. Sosnowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9842)

Abstract

In this paper a new classification solution which joins C–Fuzzy Decision Trees and Fuzzy Random Forest is proposed. Its assumptions are similar to the Fuzzy Random Forest, but instead of fuzzy trees it consists of C–Fuzzy Decision Trees. To test the proposed classifier there was performed a set of experiments. These experiments were performed using four datasets: Ionosphere, Dermatology, Pima–Diabetes and Hepatitis. Created forest was compared to C4.5 rev. 8 Decision Tree and single C–Fuzzy Decision Tree. The influence of randomness on the classification accuracy was also tested.

Keywords

Fuzzy tree C–Fuzzy Decision Tree Fuzzy random forest 

Notes

Acknowledgment

This work was supported by the grant S/WI/1/2013 from Bialystok University of Technology founded by Ministry of Science and Higher Education.

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© IFIP International Federation for Information Processing 2016

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Authors and Affiliations

  1. 1.Faculty of Computer ScienceBialystok University of TechnologyBialystokPoland

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