Movie Rating Prediction
نویسندگان
چکیده
The Internet Movie Database (IMDB) is one of the largest online resources for general movie information combined with a forum in which users can rate movies. We investigate the extent to which a movie’s average user rating can be predicted after learning the relationship between the rating and a movie’s various attributes from a training set. Two methods are evaluated: kernel regression and model trees. Modifications to standard algorithms for training these two regressors lead to better prediction accuracy on this data set.
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