TY - JOUR
T1 - Minimal inhibitory association rules for almost all k -valued information systems
AU - Delimata, Pawel
AU - Moshkov, Mikhail Ju
AU - Skowron, Andrzej
AU - Suraj, Zbigniew
N1 - Generated from Scopus record by KAUST IRTS on 2023-09-21
PY - 2009/1/1
Y1 - 2009/1/1
N2 - There are three approaches to use inhibitory rules in classifiers: (i) lazy algorithms based on an information about the set of all inhibitory rules, (ii) standard classifiers based on a subset of inhibitory rules constructed by a heuristic, and (iii) standard classifiers based on the set of all minimal (irreducible) inhibitory rules. The aim of this chapter is to show that the last approach is not feasible (from computational complexity point of view). We restrict our considerations to the class of k-valued information systems, i.e., information systems with attributes having values from {0,..., k-1}, where k >2. Note that the case k=2 was considered earlier in [51]. © 2009 Springer-Verlag Berlin Heidelberg.
AB - There are three approaches to use inhibitory rules in classifiers: (i) lazy algorithms based on an information about the set of all inhibitory rules, (ii) standard classifiers based on a subset of inhibitory rules constructed by a heuristic, and (iii) standard classifiers based on the set of all minimal (irreducible) inhibitory rules. The aim of this chapter is to show that the last approach is not feasible (from computational complexity point of view). We restrict our considerations to the class of k-valued information systems, i.e., information systems with attributes having values from {0,..., k-1}, where k >2. Note that the case k=2 was considered earlier in [51]. © 2009 Springer-Verlag Berlin Heidelberg.
UR - http://link.springer.com/10.1007/978-3-540-85638-2_3
UR - http://www.scopus.com/inward/record.url?scp=51849164490&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85638-2_3
DO - 10.1007/978-3-540-85638-2_3
M3 - Article
SN - 1860-949X
VL - 163
SP - 31
EP - 41
JO - Studies in Computational Intelligence
JF - Studies in Computational Intelligence
ER -