12110948刘焱钰

GMF.csv

@@ -0,0 +1,31 @@
+Model,HR@10,NDCG@10
+GMF,0.10438596492535189,0.4642449884038222
+GMF,0.11101973684210527,0.4617882085473914
+GMF,0.14029605263157896,0.47715529360269243
+GMF,0.19747807022772337,0.49543382399960567
+GMF,0.26403508766701345,0.5139023636516772
+GMF,0.31968201759614445,0.5272904085485559
+GMF,0.3660087718775398,0.5325772298009772
+GMF,0.3904605263157895,0.5373425558993691
+GMF,0.40657894736842104,0.5397488236427307
+GMF,0.41677631578947366,0.5441246678954677
+GMF,0.42379385954455323,0.5464331931189487
+GMF,0.4264802631578947,0.5487803227023075
+GMF,0.43125,0.5482266338248002
+GMF,0.43262061398280294,0.5501784537967883
+GMF,0.4337171052631579,0.5516256558267694
+GMF,0.4342105263157895,0.5523644961808857
+GMF,0.43486842105263157,0.5540454315511804
+GMF,0.4351973684210526,0.5542220294475555
+GMF,0.4355263157894737,0.5540746701391119
+GMF,0.4356907894736842,0.5544112961543234
+GMF,0.4363486842105263,0.5549225869931673
+GMF,0.43700657894736844,0.5548475023947264
+GMF,0.4375,0.5548983228834052
+GMF,0.4381578947368421,0.5552136079261177
+GMF,0.4384868421052632,0.5554311592327921
+GMF,0.43914473684210525,0.5551701674335882
+GMF,0.4393092105263158,0.5553232964716459
+GMF,0.4393092105263158,0.5560040712356568
+GMF,0.43914473684210525,0.5563049589332781
+GMF,0.4394736842105263,0.5559233583902058

MLP.csv

@@ -0,0 +1,121 @@
+Model,HR@10,NDCG@10
+MLP_1,0.4456140351922888,0.5563795575970097
+MLP_1,0.4457785088764994,0.5564770824030826
+MLP_1,0.446600877297552,0.5562399412456311
+MLP_1,0.4467653509817625,0.5564063160043013
+MLP_1,0.4467653509817625,0.5562657506842362
+MLP_1,0.4467653509817625,0.5565758792977584
+MLP_1,0.4467653509817625,0.556453842238376
+MLP_1,0.4469298246659731,0.556360315649133
+MLP_1,0.4469298246659731,0.5561862173833345
+MLP_1,0.4469298246659731,0.5561626892340811
+MLP_1,0.4472587720343941,0.5559077836965259
+MLP_1,0.4472587720343941,0.5560804370202517
+MLP_1,0.4474232457186046,0.5559106456606011
+MLP_1,0.4474232457186046,0.5559163915483575
+MLP_1,0.4474232457186046,0.5559039843709845
+MLP_1,0.4474232457186046,0.5559039843709845
+MLP_1,0.4472587720343941,0.5559853478481895
+MLP_1,0.4472587720343941,0.5559853478481895
+MLP_1,0.4470942983501836,0.5560673594474792
+MLP_1,0.4470942983501836,0.5560790739561382
+MLP_1,0.4470942983501836,0.5561221430176183
+MLP_1,0.4470942983501836,0.5561317745007966
+MLP_1,0.4470942983501836,0.5562705221929048
+MLP_1,0.4470942983501836,0.5562705221929048
+MLP_1,0.4470942983501836,0.5562705221929048
+MLP_1,0.4470942983501836,0.5562502522217599
+MLP_1,0.4470942983501836,0.5562398465056169
+MLP_1,0.4470942983501836,0.5562398465056169
+MLP_1,0.4470942983501836,0.5562398465056169
+MLP_1,0.4470942983501836,0.5562398465056169
+MLP_2,0.4472587720343941,0.5563064763420507
+MLP_2,0.4457785088764994,0.5575754720913736
+MLP_2,0.4462719299291309,0.5570910089894345
+MLP_2,0.4461074562449204,0.5576410864528857
+MLP_2,0.4461074562449204,0.5573103142412086
+MLP_2,0.4462719299291309,0.5572376693549909
+MLP_2,0.446600877297552,0.5569262739859129
+MLP_2,0.4464364036133414,0.5570037543773652
+MLP_2,0.446600877297552,0.5569311258039976
+MLP_2,0.446600877297552,0.5568064805708434
+MLP_2,0.4467653509817625,0.5566659202701167
+MLP_2,0.4467653509817625,0.5566939865287982
+MLP_2,0.4467653509817625,0.5565541414838088
+MLP_2,0.4469298246659731,0.5565257856720373
+MLP_2,0.4469298246659731,0.5565587376293383
+MLP_2,0.4469298246659731,0.5565587376293383
+MLP_2,0.4467653509817625,0.556490253147326
+MLP_2,0.4467653509817625,0.5564798474311828
+MLP_2,0.4467653509817625,0.5564798474311828
+MLP_2,0.4467653509817625,0.5564752428155196
+MLP_2,0.4467653509817625,0.5564752428155196
+MLP_2,0.4467653509817625,0.5564752428155196
+MLP_2,0.4467653509817625,0.5564752428155196
+MLP_2,0.4467653509817625,0.5564752428155196
+MLP_2,0.4469298246659731,0.5563749978416844
+MLP_2,0.4469298246659731,0.5563749978416844
+MLP_2,0.4469298246659731,0.5563749978416844
+MLP_2,0.4469298246659731,0.5563749978416844
+MLP_2,0.4469298246659731,0.5563806251475686
+MLP_2,0.4469298246659731,0.5564236942090486
+MLP_3,0.4462719299291309,0.5576446759073358
+MLP_3,0.4470942983501836,0.5568542784766147
+MLP_3,0.446600877297552,0.5570903640044363
+MLP_3,0.446600877297552,0.5570436901167819
+MLP_3,0.446600877297552,0.5570418862920058
+MLP_3,0.4464364036133414,0.5571527095217453
+MLP_3,0.4464364036133414,0.5571428556191294
+MLP_3,0.4464364036133414,0.5571638640604522
+MLP_3,0.446600877297552,0.5570707584682264
+MLP_3,0.446600877297552,0.5569233536720276
+MLP_3,0.446600877297552,0.5569330306429612
+MLP_3,0.4464364036133414,0.5569386077554602
+MLP_3,0.4467653509817625,0.5568149507045745
+MLP_3,0.4469298246659731,0.5567513095705132
+MLP_3,0.4470942983501836,0.5566009358355873
+MLP_3,0.4470942983501836,0.556592909913314
+MLP_3,0.4470942983501836,0.5565968707988137
+MLP_3,0.4469298246659731,0.5567070226920279
+MLP_3,0.4469298246659731,0.5564473591352764
+MLP_3,0.4469298246659731,0.5564430180348848
+MLP_3,0.4469298246659731,0.5564430180348848
+MLP_3,0.4469298246659731,0.5564326123187416
+MLP_3,0.4469298246659731,0.5564280077030784
+MLP_3,0.4469298246659731,0.5564280077030784
+MLP_3,0.4469298246659731,0.5564280077030784
+MLP_3,0.4469298246659731,0.5564280077030784
+MLP_3,0.4469298246659731,0.5564131272466559
+MLP_3,0.4469298246659731,0.5564131272466559
+MLP_3,0.4469298246659731,0.5564131272466559
+MLP_3,0.4469298246659731,0.5564131272466559
+MLP_4,0.4472587720343941,0.5573230254022699
+MLP_4,0.4470942983501836,0.5573333850032405
+MLP_4,0.4470942983501836,0.5567386153497194
+MLP_4,0.4470942983501836,0.556657655301847
+MLP_4,0.446600877297552,0.5569917998815838
+MLP_4,0.4464364036133414,0.5571311307580847
+MLP_4,0.446600877297552,0.5570085315327895
+MLP_4,0.4467653509817625,0.5569276586959236
+MLP_4,0.446600877297552,0.5569460915891747
+MLP_4,0.446600877297552,0.5570349752902984
+MLP_4,0.446600877297552,0.5570168303815942
+MLP_4,0.446600877297552,0.5571099052303716
+MLP_4,0.446600877297552,0.5571299559191654
+MLP_4,0.446600877297552,0.5571299559191654
+MLP_4,0.4467653509817625,0.5570654508314634
+MLP_4,0.4467653509817625,0.5569313817902615
+MLP_4,0.4467653509817625,0.5567553068462171
+MLP_4,0.4467653509817625,0.5567553068462171
+MLP_4,0.4470942983501836,0.5565695781456796
+MLP_4,0.4469298246659731,0.5566454724261635
+MLP_4,0.4469298246659731,0.5566374465038902
+MLP_4,0.4469298246659731,0.5566310016732466
+MLP_4,0.4469298246659731,0.5566263970575834
+MLP_4,0.4469298246659731,0.5565298507088109
+MLP_4,0.4469298246659731,0.5565255096084193
+MLP_4,0.4469298246659731,0.5565255096084193
+MLP_4,0.4469298246659731,0.5565102596031992
+MLP_4,0.4469298246659731,0.5563849386415983
+MLP_4,0.4469298246659731,0.5563700581851758
+MLP_4,0.4469298246659731,0.5563700581851758

NeuMF.csv

@@ -0,0 +1,31 @@
+Model,HR@10,NDCG@10
+NeuMF,0.4447916667712362,0.5538063309694591
+NeuMF,0.4459429825607099,0.5587665598643453
+NeuMF,0.44544956150807835,0.559753398832522
+NeuMF,0.4452850878238678,0.560041973779076
+NeuMF,0.446600877297552,0.558251712824169
+NeuMF,0.44627192992913095,0.5578570930581344
+NeuMF,0.4457785088764994,0.5586960654509695
+NeuMF,0.44610745624492043,0.5584603849210237
+NeuMF,0.4459429825607099,0.5583915290079619
+NeuMF,0.4459429825607099,0.5577109474884836
+NeuMF,0.44643640361334147,0.5573945196051346
+NeuMF,0.446600877297552,0.5573740720748901
+NeuMF,0.446600877297552,0.5575544570621691
+NeuMF,0.44643640361334147,0.5576567863163195
+NeuMF,0.4467653509817625,0.5572417202748751
+NeuMF,0.44643640361334147,0.5573038016494952
+NeuMF,0.44627192992913095,0.5573519320864426
+NeuMF,0.44627192992913095,0.5573318202244608
+NeuMF,0.446600877297552,0.5572456243791079
+NeuMF,0.446600877297552,0.5572540160856749
+NeuMF,0.44643640361334147,0.5572758991467325
+NeuMF,0.44627192992913095,0.5576106011867523
+NeuMF,0.44627192992913095,0.5577009856700897
+NeuMF,0.44643640361334147,0.5576980418280552
+NeuMF,0.44610745624492043,0.5577347836996379
+NeuMF,0.44610745624492043,0.5576465813737167
+NeuMF,0.44643640361334147,0.557455523390519
+NeuMF,0.44643640361334147,0.557432362280394
+NeuMF,0.44643640361334147,0.5573960552090093
+NeuMF,0.44643640361334147,0.5575231548986936

README.md

@@ -1,4 +1,3 @@
-
 # STA326 - Assignment 3
 
 ## Overview

evaluation.py

@@ -0,0 +1,32 @@
+import numpy as np
+import torch
+import math
+
+def evaluate(model, test_loader, negative_loader, top_k=10):
+    model.eval()
+    HR_list = []
+    NDCG_list = []
+
+    for (user_ids, pos_item_ids, _), (neg_user_ids, _, neg_item_ids) in zip(test_loader, negative_loader):
+        items = torch.cat([pos_item_ids.unsqueeze(1), neg_item_ids], dim=1)
+        user_ids = user_ids.unsqueeze(1).expand(-1, items.size(1))
+
+        user_ids = user_ids.reshape(-1)
+        item_ids = items.reshape(-1)
+        predictions = model(user_ids, item_ids).squeeze()
+        predictions = predictions.reshape(-1, 100)
+        _, indices = torch.topk(predictions, k=top_k, dim=1)
+        recommended_items = items.gather(1, indices)
+
+        HR = (recommended_items == pos_item_ids.unsqueeze(1)).any(dim=1).float()
+        HR_list.append(HR.mean().item())
+
+        relevant = (recommended_items == pos_item_ids.unsqueeze(1))
+        rank = relevant.nonzero(as_tuple=True)[1]
+        NDCG = (1 / torch.log2(rank.float() + 2)).mean().item()
+        NDCG_list.append(NDCG)
+
+    mean_HR = np.mean(HR_list)
+    mean_NDCG = np.mean(NDCG_list)
+
+    return mean_HR, mean_NDCG