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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
• 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.
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- Winter '10