Authors
Xindong Wu, Vipin Kumar, J Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J McLachlan, Angus Ng, Bing Liu, S Yu Philip, Zhi-Hua Zhou, Michael Steinbach, David J Hand, Dan Steinberg
Publication date
2008/1
Source
Knowledge and information systems
Volume
14
Issue
1
Pages
1-37
Publisher
Springer-Verlag
Description
This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These 10 algorithms cover classification, clustering, statistical learning, association analysis, and link mining, which are all among the most important topics in data mining research and development.
Total citations
Scholar articles
X Wu, V Kumar, J Ross Quinlan, J Ghosh, Q Yang… - Knowledge and information systems, 2008
X Wu, V Kumar, JR Quinlan, J Ghosh, Q Yang… - Knowledge and Information Systems Journal, Springer …, 2007
X Wu, V Kumar, JR Quinlan, J Ghosh, Q Yang… - Dec, 2007
X Wu, V Kumar, JR Quinlan, J Ghosh, Q Yang…
X Wu, V Kumar, JR Quinlan, J Ghosh, Q Yang…