A method for improving the accuracy of data mining classification algorithms

DOI10.1016/j.cor.2008.12.011zbMath1160.91325OpenAlexW2070560454MaRDI QIDQ1017461

Nikolaos Mastrogiannis, Ioannis Giannikos, Basilis Boutsinas

Publication date: 19 May 2009

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2008.12.011

zbMATH Keywords

decision rulesdata mining classification algorithmsELECTRE I method

Mathematics Subject Classification ID

Decision theory (91B06) Applications of statistics in engineering and industry; control charts (62P30) Management decision making, including multiple objectives (90B50)

Related Items (4)

ELECTRE: A comprehensive literature review on methodologies and applications ⋮ Big data analytics in supply chain management: a state-of-the-art literature review ⋮ Logical analysis of data as a tool for the analysis of probabilistic discrete choice behavior ⋮ A meta-heuristic approach for improving the accuracy in some classification algorithms

Uses Software

• ELECTRE
• UCI-ml
• C4.5
• 4eMka2

Cites Work

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• Bayesian network classifiers
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• Data mining and knowledge discovery with evolutionary algorithms
• Multicriteria methodology for decision aiding. Transl. from the French by Mark R. McCord
• A Common Framework for Describing Some Outranking Methods
• Rough sets theory for multicriteria decision analysis
• Artificial nonmonotonic neural networks

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