In the tradition of year-end lists, the Knowledge and Information Systems journal has published a list of the top 10 algorithms in data mining, as compiled based on a survey given at the IEEE International Conference on Data Mining. Here they are (along with referenced to relevant wikipedia articles):
[1] C4.5 et al.
[2] k-means
[3] Support Vector Machines
[4] Apriori
[5] EM
[6] PageRank
[7] AdaBoost
[8] kNN
[9] Naive Bayes
[10] CART
Often times, these sorts of lists can seem rather contrived, but I pleased to see that Wu and colleagues have published a well-written--and thoughtfully referenced--survey of the Machine Learning and Data Mining literature, highlighted by pseudocode and reference equations. A great read!
Monday, January 5, 2009
Top 10 Algorithms in Data Mining
Labels:
AdaBoost,
Apriori,
Articles,
CART,
EM,
kNN,
Lists Data Mining Trees k-means,
Naive Bayes,
PageRank,
SVM
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