train.csv - The training set consists of a portion of Criteo's traffic over a period of 7 days. Each row corresponds to a display ad served by Criteo. Positive (clicked) and negatives (non-clicked) examples have both been subsampled at different rates in order to reduce the dataset size. The examples are chronologically ordered.
test.csv - The test set is computed in the same way as the training set but for events on the day following the training period.
random_submission.csv - A sample submission file in the correct format.
Label - Target variable that indicates if an ad was clicked (1) or not (0).
I1-I13 - A total of 13 columns of integer features (mostly count features).
C1-C26 - A total of 26 columns of categorical features. The values of these features have been hashed onto 32 bits for anonymization purposes.
The semantic of the features is undisclosed.
When a value is missing, the field is empty.