TY - JOUR
T1 - Partial covers and inhibitory decision rules with weights
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 - In this chapter, we consider the case, where each subset, used for covering, has its own weight, and we should minimize the total weight of subsets in partial cover. The same situation is with partial inhibitory decision rules: each conditional attribute has its own weight, and we should minimize the total weight of attributes occurring in partial inhibitory decision rule. If weights of attributes characterize time complexity of attribute value computation, then we try to minimize total time complexity of computation of attributes from partial inhibitory decision rule. If weights characterize a risk of attribute value computation (as in medical or technical diagnosis), then we try to minimize total risk, etc. © 2009 Springer-Verlag Berlin Heidelberg.
AB - In this chapter, we consider the case, where each subset, used for covering, has its own weight, and we should minimize the total weight of subsets in partial cover. The same situation is with partial inhibitory decision rules: each conditional attribute has its own weight, and we should minimize the total weight of attributes occurring in partial inhibitory decision rule. If weights of attributes characterize time complexity of attribute value computation, then we try to minimize total time complexity of computation of attributes from partial inhibitory decision rule. If weights characterize a risk of attribute value computation (as in medical or technical diagnosis), then we try to minimize total risk, etc. © 2009 Springer-Verlag Berlin Heidelberg.
UR - http://link.springer.com/10.1007/978-3-540-85638-2_5
UR - http://www.scopus.com/inward/record.url?scp=51849121056&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85638-2_5
DO - 10.1007/978-3-540-85638-2_5
M3 - Article
SN - 1860-949X
VL - 163
SP - 63
EP - 79
JO - Studies in Computational Intelligence
JF - Studies in Computational Intelligence
ER -