%0 Conference Proceedings
%T Fuzzy Random Forest with C–Fuzzy Decision Trees
%+ Białystok University of Technology
%A Gadomer, Łukasz
%A Sosnowski, Zenon, A.
%Z Part 7: Decisions
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Vilnius, Lithuania
%Y Khalid Saeed
%Y Władysław Homenda
%I Springer International Publishing
%3 Computer Information Systems and Industrial Management
%V LNCS-9842
%P 481-492
%8 2016-09-14
%D 2016
%R 10.1007/978-3-319-45378-1_43
%K Fuzzy tree
%K C–Fuzzy Decision Tree
%K Fuzzy random forest
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X 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.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01637493/document
%2 https://inria.hal.science/hal-01637493/file/419526_1_En_43_Chapter.pdf
%L hal-01637493
%U https://inria.hal.science/hal-01637493
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-9842