Number of the records: 1
Comparing Rule Mining Approaches for Classification with Reasoning
- 1.
SYSNO ASEP 0494114 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Comparing Rule Mining Approaches for Classification with Reasoning Author(s) Kopp, M. (CZ)
Bajer, L. (CZ)
Jílek, M. (CZ)
Holeňa, Martin (UIVT-O) SAI, RIDSource Title ITAT 2018: Information Technologies – Applications and Theory. Proceedings of the 18th conference ITAT 2018. - Aachen : Technical University & CreateSpace Independent Publishing Platform, 2018 / Krajči S. - ISSN 1613-0073 Pages s. 52-58 Number of pages 7 s. Publication form Online - E Action ITAT 2018. Conference on Information Technologies – Applications and Theory /18./ Event date 21.09.2018 - 25.09.2018 VEvent location Plejsy Country SK - Slovakia Event type EUR Language eng - English Country DE - Germany Keywords Classification ; Comprehensibility ; Random Forest ; Rule Mining Subject RIV IN - Informatics, Computer Science OECD category Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) R&D Projects GA17-01251S GA ČR - Czech Science Foundation (CSF) Institutional support UIVT-O - RVO:67985807 EID SCOPUS 85053817998 Annotation Classification serves an important role in domains such as network security or health care. Although these domains require understanding of the classifier’s decision, there are only a few classification methods trying to justify or explain their results. Classification rules and decision trees are generally considered comprehensible. Therefore, this study compares the classification performance and comprehensibility of a random forest classifier with classification rules extracted by Frequent Item Set Mining, Logical Item Set Mining and by the Explainer algorithm, which was previously proposed by the authors. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2019 Electronic address http://ceur-ws.org/Vol-2203/52.pdf
Number of the records: 1