Task:
Your task is to predict if a user would rate Love Actually with 5 five stars based on their ratings for the 19 other movies. 

Values:
Each row in the train and test set represents one user. Each column represents one movie. All users in the dataset rated all movies in the dataset. Each entry in this dataset is binary. A value of 1 indicates a rating of 5 stars. A value of 0 indicates a rating of 1, 2, 3 or 4 stars. 

Column meaning:
Each column represents ratings for a particular movie.
Column index, Movie 
1,  3 Idiots
2,  Bourne Identity
3,  Bruce Almighty
4,  Forest Gump
5,  How to Lose a Guy in 10 Days
6,  I Robot
7,  Independence Day
8,  La Vita E Bella
9,  Lord of the Rings
10, Oceans 11
11, Patriot
12, Pearl Harbor
13, Pirates
14, Pulp Fiction
15, Rat Race
16, Shrek
17, Star Wars
18, What Women Want
19, When Harry Met Sally

Prediction:
The variable you are predicting is the binary value for the user's rating of the movie Love Actually.

Credit:
This dataset was curated by Chris Piech, but it is based on data originally made for the "Netflix Prize". The Netflix Prize data was initially retracted because of concerns over user privacy. Reed Hastings, the CEO of Netflix, gave the official thumbs up for CS109 to release this anonymized subset of data. Thanks to Matt Chen for his help in getting the Netflix Prize data.