TY - GEN
T1 - Algorithms for filtration of unordered sets of regression rules
AU - Wróbel, Łukasz
AU - Sikora, Marek
AU - Skowron, Adam
PY - 2012
Y1 - 2012
N2 - This paper presents six filtration algorithms for the pruning of the unordered sets of regression rules. Three of these algorithms aim at the elimination of the rules which cover similar subsets of examples, whereas the other three ones aim at the optimization of the rule sets according to the prediction accuracy. The effectiveness of the filtration algorithms was empirically tested for 5 different rule learning heuristics on 35 benchmark datasets. The results show that, depending on the filtration algorithm, the reduction of the number of rules fluctuates on average between 10% and 50% and in most cases it does not cause statistically significant degradation in the accuracy of predictions.
AB - This paper presents six filtration algorithms for the pruning of the unordered sets of regression rules. Three of these algorithms aim at the elimination of the rules which cover similar subsets of examples, whereas the other three ones aim at the optimization of the rule sets according to the prediction accuracy. The effectiveness of the filtration algorithms was empirically tested for 5 different rule learning heuristics on 35 benchmark datasets. The results show that, depending on the filtration algorithm, the reduction of the number of rules fluctuates on average between 10% and 50% and in most cases it does not cause statistically significant degradation in the accuracy of predictions.
KW - rule filtration
KW - rule induction
KW - rule quality measures
KW - rule-based regression
UR - https://www.scopus.com/pages/publications/84873861898
U2 - 10.1007/978-3-642-35455-7_26
DO - 10.1007/978-3-642-35455-7_26
M3 - Conference contribution
AN - SCOPUS:84873861898
SN - 9783642354540
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 284
EP - 295
BT - Multi-Disciplinary Trends in Artificial Intelligence - 6th International Workshop, MIWAI 2012, Proceedings
T2 - 6th Multi-Disciplinary International Workshop on Artificial Intelligence, MIWAI 2012
Y2 - 26 December 2012 through 28 December 2012
ER -