personal_recommendation-master.zip
(预估有个69文件)
personal_recommendation
README.md
450B
ContentBased
production
content_based.py
3KB
util
read.py
3KB
__init__.py
0B
LFM
production
lfm.py
4KB
data
ratings.txt
352KB
movies.txt
448KB
util
read.pyc
3KB
read.py
3KB
__init__.pyc
136B
__init__.py
0B
WD
production
train.py
8KB
ReadMe
68B
.DS_Store
6KB
data
test.txt
1.68MB
train.txt
3.36MB
PR
production
personal_rank.py
4KB
data
log.txt
95B
ratings.txt
352KB
movies.txt
448KB
util
read.pyc
2KB
mat_util.pyc
2KB
read.py
2KB
__init__.pyc
135B
__init__.py
0B
mat_util.py
2KB
Tree
production
run_total.sh
1KB
train.py
7KB
ana_train_data.py
5KB
check.py
6KB
__init__.py
0B
ReadMe
46B
.DS_Store
6KB
data
test.txt
1.68MB
train.txt
3.36MB
util
get_feature_num.py
340B
__init__.py
0B
LR
production
test.py
159B
run_total.sh
799B
train.py
2KB
ana_train_data.py
9KB
check.py
4KB
.DS_Store
8KB
data
test.txt
1.68MB
train.txt
3.36MB
util
get_feature_num.py
340B
__init__.py
0B
CF
production
itemcf.py
5KB
usercf.py
6KB
data
ratings.txt
352KB
movies.txt
448KB
util
reader.pyc
2KB
__init__.pyc
135B
__init__.py
0B
reader.py
2KB
Item2Vec
bin
word2vec
40KB
production
train.sh
167B
produce_train_data.py
1KB
run_total.sh
570B
produce_item_sim.py
2KB
ReadMe
188B
data
sim_result.txt
88B
sim_result_bk.txt
89B
train_data.txt
22.88MB
train_data_bk.txt
322KB
item_vec.txt
13.59MB
item_vec_bk.txt
2.66MB
ratings.txt
250.99MB
movies.txt
1.33MB
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