Top 10 Algorithms in Data Mining

I found a very interesting paper (published in 2007) from this post. The 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, Support Vector Machines (SVM), Apriori, Expectation-Maximization (EM), PageRank, AdaBoost, k-Nearest Neighbor Classification (kNN), Naive Bayes, and Classification and Regression Trees (CART). And with each algorithm, they 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. It took months for me to find and understand most of these algorithms but now you have all in one paper.

Top 10 Algorithms in Data Mining (PDF)