这是indexloc提供的服务，不要输入任何密码
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Movielens fix #7 #9

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Feb 8, 2018
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Movielens fix #7 #9

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17 changes: 14 additions & 3 deletions data_utils/movie_lense_data_converter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ def main(args):
min_ts = 100000000000
max_ts = 0
total_rating_count = 0
with open(inpt, 'r') as inpt_f:
with open(inpt, 'r') as inpt_f: #ratings.csv headers: userId,movieId,rating,timestamp
for line in inpt_f:
if 'userId' in line:
continue
Expand Down Expand Up @@ -65,19 +65,29 @@ def main(args):
training_data = dict()
validation_data = dict()
test_data = dict()
train_set_items = set()

for userId in data.keys():
if len(data[userId]) < 2:
print("WARNING")
#print("WARNING, userId {} has less than 2 ratings, skipping user...".format(userId))
continue
time_sorted_ratings = sorted(data[userId], key=lambda x: x[2]) # sort by timestamp
last_train_ind = floor(percent * len(time_sorted_ratings))
training_data[userId] = time_sorted_ratings[:last_train_ind]
for rating_item in time_sorted_ratings[:last_train_ind]:
train_set_items.add(rating_item[0]) # keep track of items from training set
p = random.random()
if p <= 0.5:
validation_data[userId] = time_sorted_ratings[last_train_ind:]
else:
test_data[userId] = time_sorted_ratings[last_train_ind:]

# remove items not not seen in training set
for userId, userRatings in test_data.items():
test_data[userId] = [rating for rating in userRatings if rating[0] in train_set_items]
for userId, userRatings in validation_data.items():
validation_data[userId] = [rating for rating in userRatings if rating[0] in train_set_items]

print("Training Data")
print_stats(training_data)
save_data_to_file(training_data, out_prefix+".train")
Expand All @@ -91,4 +101,5 @@ def main(args):


if __name__ == "__main__":
main(sys.argv)
main(sys.argv)