Reduct-Based Analysis of Decision Algorithms: Application in Computational Stylistics
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.
KeywordsDRSA Classifier Computational Stylistics Reduct Decision Algorithm Feature Selection
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