Algorithm Analysis
Introduction In their paper on the k-nearest neighbor (knn) algorithm, the BellKor team mention three choices that they considered for a similarity function: Pearson's Correlation Coefficient, the Cosine Coefficient, and the Root Mean Square Difference. In today's blog, I will focus solely on the Pearson Correlation Coefficient. It is clear from the paper that they did a lot of work with Pearson.
More data usually beats better algorithms
Datawocky On Teasing Patterns from Data, with Applications to Search, Social Media, and Advertising I teach a class on Data Mining at Stanford. Students in my class are expected to do a project that does some non-trivial data mining. Many students opted to try their hand at the Netflix Challenge: to design a movie recommendations algorithm that does better than the one developed by Netflix. Here's
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