def get_moive100k_acc_cv():
raw_data = get_moive100k()
mtrs = get_metrics_methods()
jkx = JphKfold(5, raw_data, metrics=mtrs)
mscore = jkx.cross_validate()
print mscore
return
def get_moive100k_acc_cv():
raw_data = get_moive100k()
mtrs = get_metrics_methods()
jkx = JphKfold(5,raw_data,metrics=mtrs)
mscore = jkx.cross_validate()
print mscore
return
def Generate_Simulating_Data_on_MovieLens(user_id):
user_id = int(user_id)
filelocation = "./ML100K/"
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
generate_simulating_data(raw_data,friend_data,user_id,70,10,filelocation)
def get_friends_from_ml100k():
dst_file = "./src/dataset/movie100k/ml100kfriend.dat"
if path.isfile(dst_file):
friend_data = pickle.load(open(dst_file, "rb"))
return friend_data
raw_data = get_moive100k(True)
raw_model = Model(raw_data)
cosine_sim = CosineSimilarity(raw_model)
friend_data = {}
for user_id in raw_model.get_user_ids():
neighbors = cosine_sim.get_similarities(user_id)[:250]
user_ids, x = zip(*neighbors)
user_ids = list(user_ids)
shuffle(user_ids)
# note:
# Randomly choose 150 out of 250 neighbors as friends.
# In such case, systems is able to (possiblly) choose strangers which
# are in top-250 similar users, but with a probability slightly
# smaller than friends selection.
friend_data[user_id] = user_ids[:150]
pickle.dump(friend_data, open(dst_file, "w"), protocol=2)
return friend_data
def get_friends_from_ml100k():
dst_file = "./src/dataset/movie100k/ml100kfriend.dat"
if path.isfile(dst_file):
friend_data = pickle.load(open(dst_file, "rb"))
return friend_data
raw_data = get_moive100k(True);
raw_model = Model(raw_data);
cosine_sim = CosineSimilarity(raw_model)
friend_data = {}
for user_id in raw_model.get_user_ids():
neighbors = cosine_sim.get_similarities(user_id)[:250]
user_ids, x = zip(*neighbors)
user_ids = list(user_ids)
shuffle(user_ids)
# note:
# Randomly choose 150 out of 250 neighbors as friends.
# In such case, systems is able to (possiblly) choose strangers which
# are in top-250 similar users, but with a probability slightly
# smaller than friends selection.
friend_data[user_id] = user_ids[:150]
pickle.dump(friend_data,open(dst_file, "w"),protocol=2)
return friend_data
def Generate_Simulating_Data_on_MovieLens(user_id, f_num, t_num):
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
friend_model = FriendsModel(raw_data, friend_data)
cosine_sim = CosineSimilarity(friend_model)
fs = Friends_Strangers(cosine_sim, f_num, t_num)
friends = fs.get_rand_friends(user_id)
strangers = fs.get_rand_strangers(user_id)
def Generate_Simulating_Data_on_MovieLens(user_id,f_num, t_num):
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
friend_model = FriendsModel(raw_data,friend_data)
cosine_sim = CosineSimilarity(friend_model)
fs = Friends_Strangers(cosine_sim, f_num, t_num)
friends = fs.get_rand_friends(user_id)
strangers = fs.get_rand_strangers(user_id)
def get_model():
raw_data = get_moive100k()
model = Model(raw_data)
return model
def JPH_on_MovieLens():
f_s = [20, 40, 60, 80, 100]
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
jhk_friends(raw_data, friend_data, f_s)
def Single_Stranger_Influence_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
filename = "friend_dif_ml_"
single_influence(raw_data, friend_data, False, filename)
def MAE_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
f_ts = [(10, 10), (20, 10), (30, 10), (40, 10), (50, 10), (60, 10),
(70, 10), (80, 10), (90, 10), (100, 10)]
calculate_cosine_friends_strangers(raw_data, friend_data, f_ts)
def Pure_Friend_Influence_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
filename = "pure_friend_dif_ml_"
pure_single_friend_influence(raw_data, friend_data, filename)
def get_model():
raw_data = get_moive100k()
model = Model(raw_data)
return model
def Pure_Friend_Influence_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
filename = "pure_friend_dif_ml_"
pure_single_friend_influence(raw_data,friend_data,filename)
def JPH_on_MovieLens():
f_s = [20, 40 ,60, 80, 100]
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
jhk_friends(raw_data, friend_data, f_s)
def Single_Stranger_Influence_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
filename = "friend_dif_ml_"
single_influence(raw_data,friend_data,False,filename)
def MAE_on_MovieLens():
friend_data = get_friends_from_ml100k()
raw_data = get_moive100k()
f_ts = [(10,10),(20,10),(30,10),(40,10),(50,10),(60,10),(70,10),(80,10),(90,10),(100,10)]
calculate_cosine_friends_strangers(raw_data, friend_data, f_ts)