def NDCG(results):
ndcg1 = 0
ndcg3 = 0
for result in results:
ndcg1 += ndcg_at_k(result, 1, method=1)
ndcg3 += ndcg_at_k(result, 3, method=1)
ndcg1 = ndcg1 / len(results)
ndcg3 = ndcg3 / len(results)
return str(ndcg1) + " " + str(ndcg3)
def NDCG(results):
ndcg1 = 0
ndcg3 = 0
for result in results:
ndcg1 += ndcg_at_k(result, 1, method=1)
ndcg3 += ndcg_at_k(result, 3, method=1)
ndcg1 = ndcg1 / len(results)
ndcg3 = ndcg3 / len(results)
print("NDCG@1", ndcg1)
print("NDCG@3", ndcg3)
return ndcg3
tempresult=[]
if keyd in true.keys():
pcount = 0
ncount += 1
for pred in prediction[keyd]:
pcount = pcount + 1
if keyd not in combineresults.keys():
combineresults[keyd] = []
combineresults[keyd].append((pred, pcount))
if(pred in true[keyd]):
obj = truescore[keyd]
score = obj[pred]
tempresult.append(score)
else:
tempresult.append(0)
ndcg += ndcg_at_k(tempresult,3,method=1)
ndcg1 += ndcg_at_k(tempresult, 1, method=1)
results.append(tempresult)
if(ncount > 0):
# print(ndcg,ncount)
print(ndcg/ncount)
print(ndcg1/ncount)
# print(results)
# print(ndcg_at_k(results, 1, method=1))
# print(ndcg_at_k(results, 3, method=1))
# print(ndcg_at_k(results, 5, method=1))
# print(mean_average_precision(results))