17 esl chapter 1 introduction trevor hastie and rob

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Unformatted text preview: atures with the most variation. • difficult to know how well your are doing. • different from supervised learning, but can be useful as a pre-processing step for supervised learning 18 ESL Chapter 1 — Introduction Trevor Hastie and Rob Tibshirani The Netflix prize • competition started in October 2006. Training data is ratings for 18, 000 movies by 400, 000 Netflix customers, each rating between 1 and 5 • training data is very sparse— about 98% missing • objective is to predict the rating for a set of 1 million customer-movie pairs that are missing in the training data • Netflix’s original algorithm achieved a root MSE of 0.953. The first team to achieve a 10% improvement wins 1 million dollars. • is this a supervised or unsupervised problem? 19 ESL Chapter 1 — Introduction Trevor Hastie and Rob Tibshirani Grand Prize: one million dollars, if beat Netflix’s RMSE by 10%. Competition ends Sep 21, 2009 after ≈ 3 years, two leaders, 41305 teams! Winner is BellKor’s Pragmatic Chaos. 20...
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