Tensorflow implementation of Unsupervised Deep Embedding for Clustering Analysis.
>>> pip3 install -r requirements.txt
usage: train.py [-h] [--batch-size BATCH_SIZE] [--gpu-index GPU_INDEX] optional arguments: -h, --help show this help message and exit --batch-size BATCH_SIZE Train Batch Size --gpu-index GPU_INDEX GPU Index Number
The inference.py returns the latent representation (z.tsv, meta.tsv (label information).
usage: inference.py [-h] [--gpu-index GPU_INDEX] optional arguments: -h, --help show this help message and exit --gpu-index GPU_INDEX GPU Index Number
For visualization, we use t-SNE by importing z.tsv, meta.tsv into Tensorboard.
The visualization using MNIST shows as follow.
