Skip to content

Tensorflow implementation of "Unsupervised Deep Embedding for Clustering Analysis"

Notifications You must be signed in to change notification settings

HaebinShin/dec-tensorflow

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Deep Embedding Clustering (DEC) in Tensorflow

Tensorflow implementation of Unsupervised Deep Embedding for Clustering Analysis.

Installation

>>> pip3 install -r requirements.txt

Training

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

Visualize

The inference.py returns the latent representation ($z$), and exports the 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.

About

Tensorflow implementation of "Unsupervised Deep Embedding for Clustering Analysis"

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages