def recommend(self, userID):
lista = {}
recommendations = self.movie_lens_recommender.predict_ratings(userID)
# print len(recommendations)
recommendations1 = dbt_rec(self.movie_lens_recommender.get_rated_movies(userID))
for recommendation in recommendations:
if recommendation[0] in recommendations1:
lista[recommendation[0]] = self.alpha * recommendation[1] + (1 - self.alpha) * recommendations1[recommendation[0]]
del recommendations1[recommendation[0]]
else:
lista[recommendation[0]] = self.alpha * recommendation[1]
for recommendation in recommendations1.keys():
lista[recommendation] = (1 - self.alpha) * recommendations1[recommendation]
return lista
def recommend(self, userID):
lista = {}
recommendations = self.movie_lens_recommender.predict_ratings(userID)
watched = self.movie_lens_recommender.get_rated_movies(userID)
for elem in watched:
print elem
print ""
recommendations1 = dbt_rec(watched, 500)
for recommendation in recommendations:
if recommendation[0] in recommendations1:
lista[recommendation[0]] = self.alpha * recommendation[1] + (1 - self.alpha) * recommendations1[recommendation[0]]
del recommendations1[recommendation[0]]
else:
lista[recommendation[0]] = self.alpha * recommendation[1]
for recommendation in recommendations1.keys():
lista[recommendation] = (1 - self.alpha) * recommendations1[recommendation]
return sorted(lista.iteritems(), key=operator.itemgetter(1), reverse=True)
def recommend(self, userID):
lista = {}
recommendations = self.movie_lens_recommender.predict_ratings(userID)
# print len(recommendations)
recommendations1 = dbt_rec(
self.movie_lens_recommender.get_rated_movies(userID))
for recommendation in recommendations:
if recommendation[0] in recommendations1:
lista[recommendation[0]] = self.alpha * recommendation[1] + (
1 - self.alpha) * recommendations1[recommendation[0]]
del recommendations1[recommendation[0]]
else:
lista[recommendation[0]] = self.alpha * recommendation[1]
for recommendation in recommendations1.keys():
lista[recommendation] = (
1 - self.alpha) * recommendations1[recommendation]
return lista
def recommend(self, userID):
lista = {}
recommendations = self.movie_lens_recommender.predict_ratings(userID)
watched = self.movie_lens_recommender.get_rated_movies(userID)
for elem in watched:
print elem
print ""
recommendations1 = dbt_rec(watched, 500)
for recommendation in recommendations:
if recommendation[0] in recommendations1:
lista[recommendation[0]] = self.alpha * recommendation[1] + (
1 - self.alpha) * recommendations1[recommendation[0]]
del recommendations1[recommendation[0]]
else:
lista[recommendation[0]] = self.alpha * recommendation[1]
for recommendation in recommendations1.keys():
lista[recommendation] = (
1 - self.alpha) * recommendations1[recommendation]
return sorted(lista.iteritems(),
key=operator.itemgetter(1),
reverse=True)
