The more I look at ML Libraries for clusters, the more I see limitations because of the need to meet communitive and associative constraints. I had used scikitlearn Random Forests on multi core (not clusters) and found it to be superior to SVMs for non-linear classifications with high dim. Are there any good references on what ML (Supervised/Unsupervised and Hybrid) algorithms can and cannot work on Apache-Like Clusters (Hadoop, Hbase, Spark, Accumulo) and why? Furthermore, are there any good references on what does work well currently and under what conditions? thanks Mate, Chris
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