Awesome
DCN: Deep Clustering Network
Forked from xuyxu (https://github.com/xuyxu/Deep-Clustering-Network)
Results
NMI | ARI | parameters |
---|---|---|
0.841 | 0.747 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.005 --lr 0.002 |
0.800 | 0.689 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.005 --lr 0.001 |
0.800 | 0.684 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.004 --lr 0.001 |
0.793 | 0.676 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.01 --lr 0.001 |
0.758 | 0.647 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.05 --lr 0.001 |
0.748 | 0.629 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.05 |
0.737 | 0.618 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.05 --lr 0.0001 |
0.737 | 0.595 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.05 --lr 0.0005 |
0.701 | 0.581 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 |
0.661 | 0.472 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.001 --lr 0.001 |
0.627 | 0.412 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.05 --lr 0.005 |
0.678 | 0.526 | mnist.py --latent-dim 10 --epoch 50 --pre-epoch 50 --lamda 0.1 --lr 0.001 |
0.536 | 0.205 | mnist.py --latent-dim 3 --epoch 50 --pre-epoch 50 --lamda 0.005 --lr 0.001 |
----- | ----- | ------------ |
0.81 | 0.73 | original paper claim: pre-/eps 50, lamda 0.05, 4-layer 500-500-2000-10 |