Top 10 algorithms in data mining

@article{Wu2007Top1A,
  title={Top 10 algorithms in data mining},
  author={Xindong Wu and Vipin Kumar and J. Ross Quinlan and Joydeep Ghosh and Qiang Yang and Hiroshi Motoda and Geoffrey J. McLachlan and Angus F. M. Ng and B. Liu and Philip S. Yu and Zhi-Hua Zhou and Michael S. Steinbach and David J. Hand and Dan Steinberg},
  journal={Knowledge and Information Systems},
  year={2007},
  volume={14},
  pages={1-37}
}
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. [] Key Method 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…
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