Transcription of Top 10 algorithms in data mining - UVM
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Knowl Inf Syst (2008) 14:1 37 DOI PAPERTop 10 algorithms in data miningXindong Wu Vipin Kumar J. Ross Quinlan Joydeep Ghosh Qiang Yang Hiroshi Motoda Geoffrey J. McLachlan Angus Ng Bing Liu Philip S. Yu Zhi-Hua Zhou Michael Steinbach David J. Hand Dan SteinbergReceived: 9 July 2007 / Revised: 28 September 2007 / Accepted: 8 October 2007 Published online: 4 December 2007 Springer-Verlag London Limited 2007 AbstractThis paper presents the top 10 data mining algorithms identified by the IEEEI nternational Conference on data mining (ICDM) in December 2006: ,k-Means, SVM,Apriori, EM, PageRank, AdaBoost,kNN, Naive Bayes, and CART. These top 10 algorithmsare among the most influential data mining algorithms in the research community.
Top 10 algorithms in data mining 3 After the nominations in Step 1, we verified each nomination for its citations on Google Scholar in late October 2006, and removed those nominations that did not have at least 50
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Introduction to Data Mining, Knowledge, Data, MANAGING AND MINING GRAPH DATA, Introduction, Mining, Data Preprocessing Techniques for Data Mining, Data Mining, Data Mining Applications in Higher Education, Data Mining Applications in Higher Education Introduction, Educational Data Mining and Learning Analytics, Data Mining to Insurance Customer, Data Mining to Insurance Customer Churn Management, News Detection on Social Media: A Data, News Detection on Social Media: A Data Mining Perspective, Data Preparation for Data Mining, Body of Knowledge