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Tensorflow implementation ofUnsupervised 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 thishelp message andexit --batch-size BATCH_SIZE Train Batch Size --gpu-index GPU_INDEX GPU Index Number
Theinference.py returns the latent representation (z.tsv,meta.tsv (label information).
usage: inference.py [-h] [--gpu-index GPU_INDEX]optional arguments: -h, --help show thishelp message andexit --gpu-index GPU_INDEX GPU Index Number
For visualization, we use t-SNE by importingz.tsv,meta.tsv intoTensorboard.The visualization using MNIST shows as follow.
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Tensorflow implementation of "Unsupervised Deep Embedding for Clustering Analysis"
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