@inbook{e65f0cb56e0c4cb59829bdaa7215a267,
title = "Weighting attributes and decision rules through rankings and discretisation parameters",
abstract = "Estimation of relevance for attributes can be gained by the means of their ranking, which, by calculated weights, puts variables into a specific order. A ranking of features can be exploited not only at the stage of data pre-processing, but also in post-processing exploration of properties for obtained solutions. The chapter is dedicated to research on weighting condition attributes and decision rules inferred within Classical Rough Set Approach, basing on a ranking and numbers of intervals found for features during supervised discretisation. The rule classifiers tested were employed within the stylometric analysis of texts for the task of binary authorship attribution with balanced data.",
keywords = "Authorship attribution, Condition attribute, Decision rule CRSA, Discretisation, Ranking, Stylometry",
author = "Urszula Sta{\'n}czyk",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.",
year = "2019",
doi = "10.1007/978-3-030-02357-7\_2",
language = "English",
series = "Studies in Computational Intelligence",
publisher = "Springer Verlag",
pages = "25--43",
booktitle = "Studies in Computational Intelligence",
address = "Germany",
}