Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
Dominance-Based Rough Set Approach to Reasoning About Ordinal Data
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
DRSA decision algorithm analysis in stylometric processing of literary texts
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Decision rule length as a basis for evaluation of attribute relevance
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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Computational stylistics focuses on description and quantifiable expression of linguistic styles of written documents that enables author characterisation, comparison, and attribution. It is a case when observation of subtle relationships in data sets is required, with domain knowledge uncertain. Therefore, techniques from the artificial intelligence area, such as Dominance-based Rough Set Approach (DRSA), are well suited to handle the problem. DRSA enables construction of a rule-based classifier consisting of decision rules, selection of which can greatly influence classification accuracy. The paper presents research on application of DRSA classifier in author recognition for literary texts, with considerations on the classifier performance based on an analysis of relative reducts, such subsets of features that maintain classification properties.