Titlebook: Inhibitory Rules in Data Analysis; A Rough Set Approach Pawel Delimata,Mikhail Ju. Moshkov,Zbigniew Suraj Book 2009 Springer-Verlag Berlin

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ANA

pus840

Partial Covers and Inhibitory Decision Rules,s over information systems. To this end, it is enough to fix an arbitrary attribute . of the information system as the decision attribute and study inhibitory association rules with the right-hand side of the kind .?≠?. as inhibitory decision rules over the obtained decision system (decision table).

耕種

Lazy Classification Algorithms Based on Deterministic and Inhibitory Association Rules,rmation systems ., .?∈?.(.), where .(.) is the set of values of the decision attribute in .. For .?∈?.(.), the information system . contains only objects (rows) of . with the value of the decision attribute equal to ..

前面

Lazy Classification Algorithms Based on Deterministic and Inhibitory Decision Rules, deterministic and inhibitory decision rules of the forms . respectively, where .,...,. are conditional attributes, .,...,. are values of these attributes, . is the decision attribute and . is a value of .. By .(.) we denote the set of values of the decision attribute ..

entail

Infinitesimal

Maximal Consistent Extensions of Information Systems,eted as local processes of a concurrent system, values of attributes – as states of local processes, and objects (tuples of values of attributes on objects) – as global states of the considered concurrent system..The knowledge encoded in an information system can be represented by means of true rule

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Minimal Inhibitory Association Rules for Almost All ,-Valued Information Systems,(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

Needlework

Partial Covers and Inhibitory Decision Rules,ations are based on the use of known results for partial covers..We show that:.Similar results can be obtained for partial inhibitory association rules over information systems. To this end, it is enough to fix an arbitrary attribute . of the information system as the decision attribute and study in

Efflorescent

Partial Covers and Inhibitory Decision Rules with Weights, 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 c