TY  - JOUR
AU  - Wu, Xindong
AU  - Kumar, Vipin
AU  - Quinlan, J. Ross
AU  - Ghosh, Joydeep
AU  - Yang, Qiang
AU  - Motoda, Hiroshi
AU  - McLachlan, Geoffrey
AU  - Ng, Angus
AU  - Liu, Bing
AU  - Yu, Philip
AU  - Zhou, Zhi-Hua
AU  - Steinbach, Michael
AU  - Hand, David
AU  - Steinberg, Dan
T1  - Top 10 algorithms in data mining
JO  - Knowledge and Information Systems
PY  - 2008/01
VL  - 14
IS  - 1
SP  - 1
EP  - 37
UR  - http://dx.doi.org/10.1007/s10115-007-0114-2
M3  - 
KW  - algorithm
KW  - ieee
KW  - icdm
KW  - top
KW  - data
KW  - mining
L1  - 
SN  - 
N1  - 
N1  - 
AB  - This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM)
<p>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 andfurther research on the algorithm. These 10 algorithms cover classification, clustering, statistical learning, associationanalysis, and link mining, which are all among the most important topics in data mining research and development.
ER  -