Fuzzy Random Forest with C–Fuzzy Decision Trees

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.
Type de document :
Communication dans un congrès
Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.481-492, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_43〉
Liste complète des métadonnées

Littérature citée [11 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01637493
Contributeur : Hal Ifip <>
Soumis le : vendredi 17 novembre 2017 - 15:44:57
Dernière modification le : samedi 18 novembre 2017 - 01:16:40
Document(s) archivé(s) le : dimanche 18 février 2018 - 15:58:55

Fichier

 Accès restreint
Fichier visible le : 2019-01-01

Connectez-vous pour demander l'accès au fichier

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Collections

Citation

Łukasz Gadomer, Zenon Sosnowski. Fuzzy Random Forest with C–Fuzzy Decision Trees. Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.481-492, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_43〉. 〈hal-01637493〉

Partager

Métriques

Consultations de la notice

80