![]() But there is wide variance in the data-some movies in the training set have as few as 3 ratings, while one user rated over 17,000 movies. The training set is constructed such that the average user rated over 200 movies, and the average movie was rated by over 5000 users. In order to protect the privacy of the customers, "some of the rating data for some customers in the training and qualifying sets have been deliberately perturbed in one or more of the following ways: deleting ratings inserting alternative ratings and dates and modifying rating dates." No information at all is provided about users. Quiz set (1,408,342 ratings), used to calculate leaderboard scoresįor each movie, the title and year of release are provided in a separate dataset.Test set (1,408,789 ratings), used to determine winners.Qualifying set (2,817,131 ratings) consisting of:.Training set (99,072,112 ratings not including the probe set 100,480,507 including the probe set).In summary, the data used in the Netflix Prize looks as follows: The probe, quiz, and test data sets were chosen to have similar statistical properties. Netflix also identified a probe subset of 1,408,395 ratings within the training data set. Note that, while the actual grades are integers in the range 1 to 5, submitted predictions need not be. Submitted predictions are scored against the true grades in the form of root mean squared error (RMSE), and the goal is to reduce this error as much as possible. Only the judges know which ratings are in the quiz set, and which are in the test set-this arrangement is intended to make it difficult to hill climb on the test set. The other half is the test set of 1,408,789, and performance on this is used by the jury to determine potential prize winners. A participating team's algorithm must predict grades on the entire qualifying set, but they are informed of the score for only half of the data: a quiz set of 1,408,342 ratings. The qualifying data set contains over 2,817,131 triplets of the form, with grades known only to the jury. ![]() The user and movie fields are integer IDs, while grades are from 1 to 5 ( integer) stars. Each training rating is a quadruplet of the form. ![]() Netflix provided a training data set of 100,480,507 ratings that 480,189 users gave to 17,770 movies. On September 21, 2009, the grand prize of US$1,000,000 was given to the BellKor's Pragmatic Chaos team which bested Netflix's own algorithm for predicting ratings by 10.06%. The competition was held by Netflix, a video streaming service, and was open to anyone who is neither connected with Netflix (current and former employees, agents, close relatives of Netflix employees, etc.) nor a resident of certain blocked countries (such as Cuba or North Korea). without the users being identified except by numbers assigned for the contest. The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |