Name
Title | ||
|---|---|---|
Comparison of some classification algorithms based on deterministic and nondeterministic decision rules |
Abstract | ||
|---|---|---|
We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. 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. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14467-7_5 | T. Rough Sets |
Keywords | Field | DocType |
algorithms extract,decision value,decision table,deterministic decision rule,minimal decision rule,possible decision,right hand side,nondeterministic decision rule,inhibitory rule,bounded nondeterministic rule,inhibitory decision rule,rough set,rule based,classification,polynomial time,rough sets,decision rule,decision tables | Decision tree,Optimal decision,Decision table,Computer science,Theoretical computer science,Artificial intelligence,Distributed computing,Decision rule,Admissible decision rule,Rule-based system,Nondeterministic algorithm,Machine learning,Bounded function | Journal |
Volume | ISSN | ISBN |
12 | 0302-9743 | 3-642-14466-7 |
Citations | PageRank | References |
5 | 0.55 | 22 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pawel Delimata | 1 | 38 | 3.47 |
| Barbara Marszał-Paszek | 2 | 11 | 2.28 |
| Mikhail Ju. Moshkov | 3 | 335 | 60.44 |
| Piotr Paszek | 4 | 40 | 5.95 |
| Andrzej Skowron | 5 | 5062 | 421.31 |
| Zbigniew Suraj | 6 | 501 | 59.96 |