Abstract
Decision algorithms correspond to the rule-based approach to classification and pattern recognition problems. While to shorten the processing time we need as few constituent decision rules as possible, when their number is too low it may lead to a poor performance of the classifier. The decision rules can be found by providing the minimal cover of the training samples, by calculating rules with some genetic algorithms, by the exhaustive search for all rules. This last option offers the widest choice of rules, which enables tailoring the final algorithm to the task at hand, yet this is achieved by the additional cost of rule selection process. Usually there are assumed some measures indicating the quality of individual decision rules. The paper presents a different procedure, which is closer to feature reduction. In the first step there are selected condition attributes that are discarded, then the rules that contain conditions on these attributes are removed from the algorithm. The classifier performance is observed in the domain of computational stylistics, which is a study on characteristics of writing styles.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Baszczynski, J., Sowinski, R., Szelaga, M.: Sequential covering rule induction algorithm for variable consistency rough set approaches. Information Sciences 181(5), 987–1002 (2011)
Burrows, J.: Textual analysis. In: Schreibman, S., Siemens, R., Unsworth, J. (eds.) A Companion to Digital Humanities. Blackwell, Oxford (2004)
Craig, H.: Stylistic analysis and authorship studies. In: Schreibman, S., Siemens, R., Unsworth, J. (eds.) A Companion to Digital Humanities. Blackwell, Oxford (2004)
Greco, S., Matarazzo, B., Słowiński, R.: Handling missing values in rough set analysis of multi-attribute and multi-criteria decision problems. In: Zhong, N., Skowron, A., Ohsuga, S. (eds.) RSFDGrC 1999. LNCS (LNAI), vol. 1711, pp. 146–157. Springer, Heidelberg (1999)
Greco, S., Matarazzo, B., Slowinski, R.: The use of rough sets and fuzzy sets in Multi Criteria Decision Making. In: Gal, T., Hanne, T., Stewart, T. (eds.) Advances in Multiple Criteria Decision Making, pp. 14.1–14.59. Kluwer Academic Publishers, Dordrecht Boston (1999)
Hu, X., Han, J., Lin, T.Y.: A new rough sets model based on database systems. Fundamenta Informaticae 20, 1–18 (2004)
Li, J., Cercone, N.: Introducing a rule importance measure. Transactions on Rough Sets 5, 167–189 (2006)
Moshkov, M., Piliszczuk, M., Zielosko, B.: On partial covers, reducts and decision rules with weights. Transactions on Rough Sets 6, 211–246 (2006)
Pawlak, Z.: Rough sets and intelligent data analysis. Information Sciences 147, 1–12 (2002)
Peng, R., Hengartner, H.: Quantitative analysis of literary styles. The American Statistician 56(3), 15–38 (2002)
Słowiński, R., Greco, S., Matarazzo, B.: Dominance-based rough set approach to reasoning about ordinal data. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 5–11. Springer, Heidelberg (2007)
Stańczyk, U.: Dominance-based rough set approach employed in search of authorial invariants. In: Kurzyński, M., Woźniak, M. (eds.) Computer Recognition Systems 3. AISC, vol. 57, pp. 315–323. Springer, Berlin (2009)
Stańczyk, U.: DRSA decision algorithm analysis in stylometric processing of literary texts. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS (LNAI), vol. 6086, pp. 600–609. Springer, Heidelberg (2010)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stańczyk, U. (2012). Rule-Based Approach to Computational Stylistics. In: Bouvry, P., Kłopotek, M.A., Leprévost, F., Marciniak, M., Mykowiecka, A., Rybiński, H. (eds) Security and Intelligent Information Systems. SIIS 2011. Lecture Notes in Computer Science, vol 7053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25261-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-25261-7_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25260-0
Online ISBN: 978-3-642-25261-7
eBook Packages: Computer ScienceComputer Science (R0)