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config.py
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from datasets.utils import *
config = {
"ml20m":
(
Dataset("MovieLens20M"),
{
"filename" : "datasets/ml20m/ratings.csv",
"item_id_name" : "movieId",
"user_id_name" : "userId",
"value_name" : "rating",
"timestamp_name" : "timestamp",
"min_value_to_keep" : 4.,
"user_min_support" : 5,
"set_all_values_to" : 1.,
"num_test_users": 10000,
"random_state": 42,
"load_previous_splits": False,
}
),
"netflix":
(
Dataset("NetflixPrize"),
{
"filename" : "datasets/netflix/netflix.csv",
"value_name" : "rating",
"timestamp_name" : "timestamp",
"min_value_to_keep" : 4.,
"user_min_support" : 5,
"set_all_values_to" : 1.,
"num_test_users": 40000,
"random_state": 42,
"load_previous_splits":False
}
),
"goodbooks":
(
Dataset("Goodbooks-10k"),
{
"raw_data" : """pd.read_csv("datasets/goodbooks/ratings.csv")""",
"user_id_name":"user_id",
"item_id_name":"book_id",
"value_name":"rating",
"min_value_to_keep" : 4.,
"user_min_support" : 5,
"item_min_support" : 1,
"set_all_values_to" : 1.,
"num_test_users": 2500,
"random_state": 42,
"load_previous_splits": False
}
),
"msd":
(
Dataset("MillionSongDataset"),
{
"raw_data" : """pd.read_csv("datasets/msd/msd_train_triplets.tsv", sep="\t", header=None)""",
"user_id_name":0,
"item_id_name":1,
"value_name" : 2,
"user_min_support" : 20,
"item_min_support" : 200,
"set_all_values_to" : 1.
}
),
"amazon":
(
Dataset("Amazon"),
{
"raw_data" : """pd.read_feather("datasets/amazon/rating_all.feather")""",
"value_name" : "rating",
"timestamp_name" : "timestamp",
"min_value_to_keep" : 4.,
"user_min_support" : 5,
"item_min_support" : 5,
"set_all_values_to" : 1.,
"num_test_users": 50000,
"random_state": 42,
"max_steps": 1000
}
),
"amazon-small":
(
Dataset("Amazon"),
{
"raw_data" : """pd.read_feather("datasets/amazon/rating_all.feather")""",
"value_name" : "rating",
"timestamp_name" : "timestamp",
"min_value_to_keep" : 4.,
"user_min_support" : 5,
"item_min_support" : 20,
"set_all_values_to" : 1.,
"num_test_users": 10000,
"random_state": 42,
"max_steps": 1000
}
),
"amazon-books":
(
Dataset("Amazon Books"),
{
"raw_data" : """pd.read_feather("datasets/amazon/books/interactions_pu20_pi20.feather")""",
"value_name" : "value",
"timestamp_name" : "timestamp",
"min_value_to_keep" : 1.,
"user_min_support" : 20,
"item_min_support" : 20,
"set_all_values_to" : 1.,
"num_test_users": 10000,
"random_state": 42,
"max_steps": 1000
}
),
}