if len(games) < i + 1:
games.append([])
user_id = d[0]
dct[d[1]] = d[4]
if d[4] == "1":
games[i].append(d[1])
# Correctly recommended games / all recommended games
avg_prec = 0.0
# Correctly recommended games / all games that should have been recommended
avg_recall = 0.0
j = 0
for i in range(len(games) - 1):
if len(games[i]) < 2: continue
r = Recommend("Frequent_Itemsets.txt")
r.set_user_games(games[i])
recommended = r.recommend()
# Caluclate Precision and recall.
all_rec = len(recommended)
should_rec = 0
correct = 0
for key in final_dict[i]:
game = key.split('"')[1]
if final_dict[i][key] == "0":
should_rec += 1
if game in recommended:
correct += 1
if should_rec == 0 or all_rec == 0:
continue
prec = float(float(correct) / float(all_rec))
recall = float(float(correct) / float(should_rec))
