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Python Implementation of Weakly Supervised Clustering article

License: Apache License 2.0

Python 100.00%
clustering numpy python sparse-matrix weak-supervision weakly-supervised-learning mnist mnist-classification mnist-dataset

weaklysupervisedclustering's Introduction

Learning Facial Action Units from Web Images with Scalable Weakly Supervised Clustering

A Python implementation

Implements train_toy.py where the toy dataset and makemoons (sklearn) generated datasets can be runned. Also now support mnist (mnist package installation required) training and olivetti faces from public dataset clustering with 40 clusters.

Requirements

  • scipy
  • numpy
  • python 3.*
  • sklearn
  • mnist (optional for train_mnist.py)

Running the repo

Run either of these files

Result (on toy dataset)

result.png

References

Article

Original implementation in Matlab:

Bonus:

Adam Optimizer added, with amsgrad (default to True)

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