Playlist prediction with recurrent neural networks on Cornell Playlist Data Set
Experiments with Softmax outputs
Model Name |
func |
func_1 |
func_2 |
func_3 |
func_4 |
func_5 |
SimpleGRU |
29.64% |
42.83% |
59.58% |
70.79% |
77.60% |
82.07% |
BiLSTM |
30.16% |
43.52% |
60.52% |
71.56% |
78.38% |
82.85% |
BiLSTM_with_Attention |
31.42% |
44.32% |
60.75% |
71.85% |
78.36% |
82.65% |
Model Name |
func |
func_1 |
func_2 |
func_3 |
func_4 |
func_5 |
SimpleGRU |
17.55% |
26.16% |
37.59% |
45.82% |
52.10% |
57.11% |
BiLSTM |
18.26% |
27.16% |
39.05% |
47.47% |
53.92% |
59.24% |
BiLSTM_with_Attention |
20.74% |
29.83% |
41.46% |
49.85% |
56.38% |
61.69% |
Model Name |
func |
func_1 |
func_2 |
func_3 |
func_4 |
func_5 |
BiLSTM_with_Attention |
28.50% |
38.85% |
52.79% |
62.27% |
68.63% |
73.63% |
Experiments with Word2Vec embeddings as inputs and outputs
Model Name |
mae |
mse |
acc |
mape |
cosine_proximity |
categorical_crossentropy |
Details |
SimpleGRU |
0.59 |
0.74 |
0.25 |
313.03 |
-0.65 |
-40.60 |
Notebook |
BiLSTM |
0.59 |
0.74 |
0.26 |
499.65 |
-0.66 |
-37.26 |
Notebook |