SYMBOL INDEX (55 symbols across 9 files)

FILE: ItemCF.py
  class ItemBasedCF (line 24) | class ItemBasedCF:
    method __init__ (line 30) | def __init__(self, k_sim_movie=20, n_rec_movie=10, use_iuf_similarity=...
    method fit (line 42) | def fit(self, trainset):
    method recommend (line 71) | def recommend(self, user):
    method test (line 101) | def test(self, testset):
    method predict (line 147) | def predict(self, testset):

FILE: LFM.py
  class LFM (line 24) | class LFM:
    method __init__ (line 30) | def __init__(self, K, epochs, alpha, lamb, n_rec_movie=10, save_model=...
    method init_model (line 54) | def init_model(self, users_set, items_set, K):
    method init_users_items_set (line 69) | def init_users_items_set(self, trainset):
    method gen_negative_sample (line 87) | def gen_negative_sample(self, items: dict):
    method predict (line 106) | def predict(self, user, item):
    method train (line 120) | def train(self, trainset):
    method fit (line 139) | def fit(self, trainset):
    method recommend (line 164) | def recommend(self, user):
    method test (line 179) | def test(self, testset):

FILE: UserCF.py
  class UserBasedCF (line 21) | class UserBasedCF:
    method __init__ (line 27) | def __init__(self, k_sim_user=20, n_rec_movie=10, use_iif_similarity=F...
    method fit (line 39) | def fit(self, trainset):
    method recommend (line 67) | def recommend(self, user):
    method test (line 97) | def test(self, testset):
    method predict (line 143) | def predict(self, testset):

FILE: dataset.py
  class DataSet (line 44) | class DataSet:
    method __init__ (line 51) | def __init__(self):
    method load_dataset (line 55) | def load_dataset(cls, name='ml-100k'):
    method parse_line (line 80) | def parse_line(cls, line: str, sep: str):
    method train_test_split (line 98) | def train_test_split(cls, ratings, test_size=0.2):

FILE: main.py
  function run_model (line 19) | def run_model(model_name, dataset_name, test_size=0.3, clean=False):
  function recommend_test (line 57) | def recommend_test(model, user_list):

FILE: most_popular.py
  class MostPopular (line 23) | class MostPopular:
    method __init__ (line 29) | def __init__(self, n_rec_movie=10, save_model=True):
    method fit (line 39) | def fit(self, trainset):
    method recommend (line 67) | def recommend(self, user):
    method test (line 85) | def test(self, testset):
    method predict (line 132) | def predict(self, testset):

FILE: random_pred.py
  class RandomPredict (line 22) | class RandomPredict:
    method __init__ (line 28) | def __init__(self, n_rec_movie=10, save_model=True):
    method fit (line 38) | def fit(self, trainset):
    method recommend (line 63) | def recommend(self, user):
    method test (line 81) | def test(self, testset):
    method predict (line 127) | def predict(self, testset):

FILE: similarity.py
  function calculate_user_similarity (line 18) | def calculate_user_similarity(trainset, use_iif_similarity=False):
  function calculate_item_similarity (line 92) | def calculate_item_similarity(trainset, use_iuf_similarity=False):
  function calculate_movie_popular (line 152) | def calculate_movie_popular(trainset):

FILE: utils.py
  class LogTime (line 16) | class LogTime:
    method __init__ (line 25) | def __init__(self, print_step=20000, words=''):
    method count_time (line 38) | def count_time(self):
    method finish (line 50) | def finish(self):
    method get_curr_step (line 58) | def get_curr_step(self):
    method get_total_time (line 61) | def get_total_time(self):
  class ModelManager (line 65) | class ModelManager:
    method __init__ (line 75) | def __init__(cls, dataset_name=None, test_size=0.3):
    method save_model (line 83) | def save_model(self, model, save_name: str):
    method load_model (line 96) | def load_model(self, model_name: str):
    method clean_workspace (line 109) | def clean_workspace(clean=False):