Paper Info
Title
Nondeterministic Decision Rules in Rule-Based Classifier.
Abstract
In the paper is discussed the truncated nondeterministic rules and their role in an evaluation of classification model. The nondeterministic rules are created as the result of shorting deterministic rules in accordance with the principle of minimum description length (MDL). As deterministic rules in database we treat the full objects description in a meaning of descriptors conjunction. The nondeterministic rules are calculated in polynomial time by using greedy strategy. The classification model is composed in two steps process. In the first step deterministic and nondeterministic rules are constructed. Next these rules are used for classifier evaluation. The evaluation results are compared with classifiers only based on deterministic rules creating by different algorithms. The experiments shows that such nondeterministic rules could be treat as an extra knowledge about data. This knowledge is able to improve the classification quality. It should be pointed out that classification process requires tuning some of their parameters relative to analyzed data.
Year
DOI
Venue
2014
10.1007/978-3-319-06932-6_18
Communications in Computer and Information Science
Keywords
Field
DocType
classification,decision tables,nondeterministic decision rules,rough sets,rule-based classifier
Decision rule,Rule based classifier,Decision table,Nondeterministic algorithm,Computer science,Minimum description length,Algorithm,Rough set,Time complexity
Conference
Volume
ISSN
Citations 
424
1865-0929
0
PageRank 
References 
Authors
0.34
10
2
Name
Order
Citations
PageRank
Piotr Paszek1405.95
Barbara Marszal-Paszek211.04