Load the preprocessed Rotten Tomatoes dataset. This version can be used as a simple matrix-like pool.
This dataset is best suited for text classification.
The training dataset contains 32712 objects. Each object is described by 22 columns of numerical, categorical and text features. The label column is not precisely specified. The dataset contains movie reviews. Every object in the dataset represents a unique review from a user and movie-specific information (such as synopsis, rating, etc.).
The validation dataset contains 8179 objects. The structure is identical to the training dataset.
Method call format
Type of return value
A two pandas.DataFrame tuple (for train and validation datasets).
from catboost.datasets import rotten_tomatoes rotten_tomatoes_train, rotten_tomatoes_test = rotten_tomatoes() print(rotten_tomatoes_train.head(3))
The output of this example:
id synopsis rating_MPAA genre ... publisher date date_int rating_10 0 830.0 A gay New Yorker stages a marriage of convenie... R Art House and International | Comedy | Drama |... ... Las Vegas Review-Journal 2004-04-16 20040416.0 8.0 1 1161.0 Screenwriter Nimrod Antal makes an impressive ... R Action and Adventure | Art House and Internati... ... E! Online 2005-04-22 20050422.0 6.0 2 596.0 "Arctic Tale" is an epic adventure that explor... G Documentary | Special Interest ... New York Daily News 2007-07-27 20070727.0 6.0 [3 rows x 22 columns]