@inproceedings{4ddd87c7944d432c9cfb70e11570f85f,
title = "Weighting and pruning of decision rules by attributes and attribute rankings",
abstract = "Pruning is a popular post-processing mechanism used in search for optimal solutions when there is insufficient domain knowledge to either limit learning data or govern induction in order to infer only the most interesting or important decision rules. Filtering of generated rules can be driven by various parameters, for example explicit rule characteristics. The paper presents research on pruning rule sets by two approaches involving attribute rankings, the first relaying on selection of rules referring to the highest ranking attributes, which is compared to weighting of rules by calculated quality measures dependent on weights coming from attribute rankings that results in rule ranking.",
keywords = "Attribute, Decision rules, Pruning, Ranking, Weighting",
author = "Urszula Sta{\'n}czyk",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2016.; 31st International Symposium on Computer and Information Sciences, ISCIS 2016 ; Conference date: 27-10-2016 Through 28-10-2016",
year = "2016",
doi = "10.1007/978-3-319-47217-1\_12",
language = "English",
isbn = "9783319472164",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "106--114",
editor = "Ricardo Lent and Erol Gelenbe and Tadeusz Czach{\'o}rski and Krzysztof Grochla",
booktitle = "Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings",
address = "Germany",
}