Mercurial > hg > hybrid-music-recommender-using-content-based-and-social-information
diff Code/eda.py @ 27:ae650489d3a8
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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--- a/Code/eda.py Wed Aug 26 02:00:48 2015 +0100 +++ b/Code/eda.py Sun Aug 30 15:49:27 2015 +0100 @@ -219,7 +219,7 @@ # fn += 1 # elif score <= rating_threshold and sim_value < EDA_treshold: # tn += 1 - print tp, fp, fn, tn + #print tp, fp, fn, tn if tp != 0: precision = tp / (tp + fp) recall = tp / (tp + fn) @@ -263,7 +263,7 @@ elapsed_time = time.time() - start_time print 'Training execution time: %.3f seconds' % elapsed_time - pi, ri, fi, ai = evaluate_eda(profile_u, users_test[i]) + pi, ri, fi, ai = evaluate_eda(profile_u, users_test[i], N=20) p = np.append(p, pi) r = np.append(r, ri) f = np.append(f, fi)