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comparison Code/content_based.py @ 27:ae650489d3a8

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Updated report
author Paulo Chiliguano <p.e.chiilguano@se14.qmul.ac.uk>
date Sun, 30 Aug 2015 15:49:27 +0100
parents e4bcfe00abf4
children
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26:e4bcfe00abf4 27:ae650489d3a8
110 else: 110 else:
111 if rating > rating_threshold: 111 if rating > rating_threshold:
112 fn += 1 112 fn += 1
113 elif rating <= rating_threshold: 113 elif rating <= rating_threshold:
114 tn += 1 114 tn += 1
115 print tp, fp, fn, tn 115 #print tp, fp, fn, tn
116 if tp != 0: 116 if tp != 0:
117 precision = tp / (tp + fp) 117 precision = tp / (tp + fp)
118 recall = tp / (tp + fn) 118 recall = tp / (tp + fn)
119 F1 = 2 * precision * recall / (precision + recall) 119 F1 = 2 * precision * recall / (precision + recall)
120 else: 120 else:
136 start_time = time.time() 136 start_time = time.time()
137 sim_matrix = build_model_cb(users_train[i]) 137 sim_matrix = build_model_cb(users_train[i])
138 138
139 topN = {} 139 topN = {}
140 for user, song_rating in users_train[i].iteritems(): 140 for user, song_rating in users_train[i].iteritems():
141 topN[user] = top_n(sim_matrix, user, song_rating) 141 topN[user] = top_n(sim_matrix, user, song_rating, rating_threshold=2, N=20)
142 elapsed_time = time.time() - start_time 142 elapsed_time = time.time() - start_time
143 print 'Training execution time: %.3f seconds' % elapsed_time 143 print 'Training execution time: %.3f seconds' % elapsed_time
144 144
145 pi, ri, fi, ai = evaluate_cb(topN, users_test[i]) 145 pi, ri, fi, ai = evaluate_cb(topN, users_test[i])
146 146