def get_performance(user_pos_test, r, auc, Ks):
'''
:param user_pos_test: user 测试集中真实交互的item
:param r: r = [1,0,1] 表示预测TOP-K是否命中
:param auc: auc =0 标量
:param Ks: TOP-K
:return:
'''
precision, recall, ndcg, hit_ratio, MAP = [], [], [], [], []
for K in Ks:
precision.append(metrics.precision_at_k(r, K))
recall.append(metrics.recall_at_k(r, K, len(user_pos_test)))
ndcg.append(metrics.ndcg_at_k(r, K))
hit_ratio.append(metrics.hit_at_k(r, K))
MAP.append(metrics.AP_at_k(r, K, len(user_pos_test)))
return {'recall': np.array(recall), 'precision': np.array(precision), 'ndcg': np.array(ndcg),
'hit_ratio': np.array(hit_ratio), 'MAP': np.array(MAP), 'auc': auc}
# calculate metrics
precision_k = np.mean(
[precision_at_k(r, args.topk) for r in preds.values()])
fnl_precision.append(precision_k)
recall_k = np.mean([
recall_at_k(r, len(test_ur[u]), args.topk)
for u, r in preds.items()
])
fnl_recall.append(recall_k)
map_k = map_at_k(list(preds.values()))
fnl_map.append(map_k)
ndcg_k = np.mean([ndcg_at_k(r, args.topk) for r in preds.values()])
fnl_ndcg.append(ndcg_k)
hr_k = hr_at_k(list(preds.values()), list(preds.keys()), test_ur)
fnl_hr.append(hr_k)
mrr_k = mrr_at_k(list(preds.values()))
fnl_mrr.append(mrr_k)
gc.collect()
for i in range(len(val_kpi)):
print(f'Validation [{i + 1}] Precision@{args.topk}: {val_kpi[i]}')
print('---------------------------------')
print(f'Precision@{args.topk}: {np.mean(fnl_precision)}')
'item'].values.tolist()
for u in preds.keys():
preds[u] = [1 if e in test_ur[u] else 0 for e in preds[u]]
# calculate metrics
precision_k = np.mean([precision_at_k(r, k) for r in preds.values()])
fnl_precision.append(precision_k)
recall_k = np.mean(
[recall_at_k(r, len(test_ur[u]), k) for u, r in preds.items()])
fnl_recall.append(recall_k)
map_k = map_at_k(list(preds.values()))
fnl_map.append(map_k)
ndcg_k = np.mean([ndcg_at_k(r, k) for r in preds.values()])
fnl_ndcg.append(ndcg_k)
hr_k = hr_at_k(list(preds.values()), list(preds.keys()), test_ur)
fnl_hr.append(hr_k)
mrr_k = mrr_at_k(list(preds.values()))
fnl_mrr.append(mrr_k)
print('---------------------------------')
print(f'Precision@{args.topk}: {np.mean(fnl_precision)}')
print(f'Recall@{args.topk}: {np.mean(fnl_recall)}')
print(f'MAP@{args.topk}: {np.mean(fnl_map)}')
print(f'NDCG@{args.topk}: {np.mean(fnl_ndcg)}')
print(f'HR@{args.topk}: {np.mean(fnl_hr)}')
print(f'MRR@{args.topk}: {np.mean(fnl_mrr)}')
