Keras implementation for ICML-2016 paper:
- Junyuan Xie, Ross Girshick, and Ali Farhadi. Unsupervised deep embedding for clustering analysis. ICML 2016.
-
Install Keras v2.0, scikit-learn and git
sudo pip install keras scikit-learn
sudo apt-get install git -
Clone the code to local.
git clone https://github.com/XifengGuo/DEC.git DEC -
Prepare datasets.
cd DEC/data/usps bash ./download_usps.sh cd ../reuters bash ./get_data.sh cd ../.. -
Run experiment on MNIST.
python DEC.py mnist
or (if there's pretrained autoencoder weights)
python DEC.py mnist --ae_weights ae_weights/mnist_ae_weights.h5
The DEC model will be saved to "results/DEC_model_final.h5". -
Run experiment on USPS.
python DEC.py usps --update_interval 30
or
python DEC.py usps --ae_weights ae_weights/usps_ae_weights --update_interval 30 -
Run experiment on REUTERSIDF10K.
python DEC.py reutersidf10k --n_clusters 4 --update_interval 20
or
python DEC.py reutersidf10k --ae_weights ae_weights/reutersidf10k_ae_weights --n_clusters 4 --update_interval 20
Original code (Caffe): https://github.com/piiswrong/dec
MXNet implementation: https://github.com/dmlc/mxnet/blob/master/example/dec/dec.py
Keras implementation without pretraining code: https://github.com/fferroni/DEC-Keras