Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Handbook of Neural Computation
Handbook of Neural Computation
Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Consistency-based search in feature selection
Artificial Intelligence
Information extraction with term frequencies
HLT '01 Proceedings of the first international conference on Human language technology research
Dominance-Based Rough Set Approach to Reasoning About Ordinal Data
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
On Covering Attribute Sets by Reducts
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Rough Set Theory: A True Landmark in Data Analysis
Rough Set Theory: A True Landmark in Data Analysis
Evaluating Importance of Conditions in the Set of Discovered Rules
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
The Structure of Style: Algorithmic Approaches to Understanding Manner and Meaning
The Structure of Style: Algorithmic Approaches to Understanding Manner and Meaning
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
Reduct-based analysis of decision algorithms: application in computational stylistics
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Application of DRSA-ANN classifier in computational stylistics
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Rule quality measures in creation and reduction of data rule models
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Rough set-based analysis of characteristic features for ANN classifier
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Incremental versus non-incremental rule induction for multicriteria classification
Transactions on Rough Sets II
Special issue recent advances in soft computing: Theories and applications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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Knowledge discovered from data can be represented in a form of decision rules, consisting of required conditions and decisions to which they lead. The quality of rules is usually considered in terms of some quantitative measures such as confidence, support or length. Depending on all these parameters the constructed classifiers can greatly vary in the predictive accuracy and the size of their structure. Both these elements depend strongly on the choice of characteristic features, which can be found by some independent feature selection procedure, but also by applying a wrapper model. In the wrapper model the classifier and its parameters are used to evaluate the importance of attributes. In the paper there are proposed measures of attribute relevance based on rule lengths. The usefulness of the described methodology is shown for rule-based classifiers, obtained through Dominance-Based Rough Set Approach, and a connectionist solution implemented with Artificial Neural Networks, both employed in the task of authorship attribution.