TY - GEN
T1 - Fuzzy rules generation method for classification problems using rough sets and genetic algorithms
AU - Sikora, Marek
PY - 2005
Y1 - 2005
N2 - A method of constructing a classifier that uses fuzzy reasoning is described in this paper. Rules for this classifier are obtained by means of algorithms relying on a tolerance rough sets model. Got rules are in so called sharp" form, a genetic algorithm is used for fuzzification of these rules. Presented results of experiments show that the proposed method allows getting a smaller rules set with similar (or better) classification abilities.
AB - A method of constructing a classifier that uses fuzzy reasoning is described in this paper. Rules for this classifier are obtained by means of algorithms relying on a tolerance rough sets model. Got rules are in so called sharp" form, a genetic algorithm is used for fuzzification of these rules. Presented results of experiments show that the proposed method allows getting a smaller rules set with similar (or better) classification abilities.
UR - https://www.scopus.com/pages/publications/33645979689
U2 - 10.1007/11548669_40
DO - 10.1007/11548669_40
M3 - Conference contribution
AN - SCOPUS:33645979689
SN - 3540286535
SN - 9783540286530
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 383
EP - 391
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005
Y2 - 31 August 2005 through 3 September 2005
ER -