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Code for reproducing experiments on MNIST and CIFAR-10 in paper "Positive-Unlabeled Learning with Non-Negative Risk Estimator".

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nnpu_tf

Code for reproducing experiments on MNIST and CIFAR-10 in paper "Positive-Unlabeled Learning with Non-Negative Risk Estimator".

Requirements

  • Python 3.6.1
  • tensorflow 1.4
  • matplotlib
  • numpy
  • sklearn

Usage

  • MNIST experiment: python train.py mnist 1

  • CIFAR-10 experiment: python train.py cifar10 1

When they are done, a figure will show up. And results are saved in the folder ./result, then you can see the figures if you run python show_result.py mnist or python show_result.py cifar10.

Result

  • Result of MNIST experiment:

Experiment MNIST

  • Result of CIFAR-10 experiment:

Experiment CIFAR-10

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Code for reproducing experiments on MNIST and CIFAR-10 in paper "Positive-Unlabeled Learning with Non-Negative Risk Estimator".

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