Title
Comparison of lazy classification algorithms based on deterministic and inhibitory decision rules
Abstract
In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules.
Year
DOI
Venue
2008
10.1007/978-3-540-79721-0_13
RSKT
Keywords
Field
DocType
decision table,algorithms extract,polynomial time complexity,deterministic decision rule,decision-making procedure,direct generation,reported result,lazy classification algorithm,new object,inhibitory decision rule,polynomial time,rough set,decision rule
Decision rule,Admissible decision rule,Decision tree,Optimal decision,Decision table,Pattern recognition,Computer science,Weighted sum model,Artificial intelligence,Statistical classification,Machine learning,Dominance-based rough set approach
Conference
Volume
ISSN
ISBN
5009
0302-9743
3-540-79720-3
Citations 
PageRank 
References 
6
0.60
9
Authors
4
Name
Order
Citations
PageRank
Paweł Delimata160.60
Mikhail Ju. Moshkov233560.44
Andrzej Skowron35062421.31
Zbigniew Suraj450159.96