@inproceedings{742d3d8770cf4cdb92ff22eff2e450dd,
title = "Weighting of attributes in an embedded rough approach",
abstract = "In an embedded approach to feature selection and reduction, a mechanism determining their choice constitutes a part of an inductive learning algorithm, as happens for example in construction of decision trees, artificial neural networks with pruning, or rough sets with activated relative reducts. The paper presents the embedded solution based on assumed weights for reducts and measures defined for conditional attributes, where weighting of these attributes was used in their backward elimination for rule classifiers induced in Dominance-Based Rough Set Approach. The methodology is illustrated with a binary classification case of authorship attribution.",
keywords = "Authorship attribution, DRSA, Embedded approach, Feature selection, Reduction, Reducts, Stylometry, Weighting",
author = "Urszula St{\'a}nczyk",
note = "Publisher Copyright: {\textcopyright} Springer India 2014.; 3rd International Conference on Man-Machine Interactions, ICMMI 2013 ; Conference date: 22-10-2013 Through 25-10-2013",
year = "2014",
doi = "10.1007/978-3-319-02309-0\_52",
language = "English",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "475--483",
editor = "Aleksandra Gruca and Tadeusz Czach{\'o}rski and Stanis{\l}aw Kozielski and Tadeusz Czach{\'o}rski",
booktitle = "Man-Machine Interactions 3",
address = "Germany",
}