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Even if the core of the algorithm is released, there can still exist better proprietary implementations. Google Pagerank, Random Forests, ROOT/SIFT, etc are exa
by huac 11y ago
Even if the core of the algorithm is released, there can still exist better proprietary implementations. Google Pagerank, Random Forests, ROOT/SIFT, etc are examples of 'best in field' algorithms that aren't available for free, public use.
- GFK_of_xmaspast 11y agoPagerank is just an eigenvector calculation, and for a sparse graph it's linear in |V|+|E|. It's pretty easy to implement, I don't know what kinds of improvements you'd want. There's a ton of random forest implementations out there, what's the closed one that's so much better? Also rootSIFT is patented so good luck with that.
- huac 11y agoGoogle has all sorts of stuff built on top of PageRank for their search engine - it's probably safe to say that their implementation is thus 'better' than the released algorithm. One of the RF creators consults with a company (http://www.salford-systems.com/products/randomforests http://www.salford-systems.com/products/randomforests) on, I suppose, better implementations. Some people have claimed it's better than the R implementation, I don't know. RootSIFT being patented is kind of my point - the authors created a (good) algorithm and haven't released it for free use. It's within these kinds of niches that Algorithmia can succeed.
- GFK_of_xmaspast 11y agoI think there's some confusion. Pagerank is the leading eigenvector of the graph (G+1x) where G is an input graph and x is a weighting term. This is not at all the same as modern Google ranking techniques, such as Panda, Penguin, and Hummingbird.