One of the interesting questions is: "what are the most useful machine learning algorithms?".

I did a little survey by looking at the Mahout user mailing list and counting occurrences of keywords. The results I got are shown in the plot above.

It seems that matrix factorization (SVD) is the most widely used algorithm, and then K-means. We have just implemented SVD as a part of the GraphLab Collaborative Filtering library. Anyone who wants to beta test it is welcome!

Nice :) But maybe this is a plot of inverse quality of the documentation for each algorithm?

ReplyDeleteI think you are wrong - for Mahout's SVD we would get division by zero.. :-)

ReplyDeleteI think that this is definitely not a measure of usage. From my experience, the order in descending frequency would be recommendations, K-means, SGD, SVD and frequent itemsets. The first two or three dominate. The order of the later ones is uncertain.

ReplyDeletenice, added to the list http://www.quora.com/What-are-the-top-10-data-mining-or-machine-learning-algorithms

ReplyDeleteThanks!

ReplyDelete- Danny Bickson