NDLI: Rule quality measures settings in a sequential covering rule induction algorithm - an empirical approach

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2015 Federated Conference on Computer Science and Information Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 5 [Editors]

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Rule quality measures settings in a sequential covering rule induction algorithm - an empirical approach

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2014 Federated Conference on Computer Science and Information Systems

2013 Federated Conference on Computer Science and Information Systems

2012 Federated Conference on Computer Science and Information Systems (FedCSIS)

2011 Federated Conference on Computer Science and Information Systems (FedCSIS)

Rule quality measures settings in a sequential covering rule induction algorithm - an empirical approach

Content Provider	IEEE Xplore Digital Library
Author	Michalak, M. Sikora, M. Wrobel, L.
Copyright Year	2015
Description	Author affiliation: Inst. of Innovative Technol. EMAG, Katowice, Poland (Wrobel, L.) \|\| Inst. of Inf., Silesian Univ. of Technol., Gliwice, Poland (Michalak, M.; Sikora, M.)
Abstract	The paper presents the results of research related to the efficiency of the so called rule quality measures which are used to evaluate the quality of rules at each stage of the rule induction. The stages of rule growing and pruning were considered along with the issue of conflicts resolution which may occur during the classification. The work is the continuation of research on the efficiency of quality measures employed in sequential covering rule induction algorithm. In this paper we analyse only these quality measures (9 measures) which had been recognised as effective based on previously conducted research.
Starting Page	109
Ending Page	118
File Size	346651
Page Count	10
File Format	PDF
ISSN	23005963
e-ISBN	9788360810651
DOI	10.15439/2015F388
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-13
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Polish Information Processing Society (PIPS)
Subject Keyword	Training Algorithm design and analysis Weight measurement Accuracy Current measurement Chlorine Prediction algorithms
Content Type	Text
Resource Type	Article

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