# mmd-critic
[](https://github.com/yourusername/mmd-critic/blob/main/LICENSE)
A Python package for implementing the Maximum Mean Discrepancy Critic (MMD-Critic) method. This method is commonly used to find prototypes and criticisms (outliers, roughly speaking) in datasets.
## Installation
You can install the package via pip:
```bash
pip install mmd-critic
```
## Usage
```python
from mmd_critic import MMDCritic
from mmd_critic.kernels import RBFKernel
critic = MMDCritic(X, RBFKernel(sigma=1), criticism_kernel=RBFKernel(2), labels=y)
protos, proto_labels = critic.select_prototypes(50)
criticisms, criticism_labels = critic.select_criticisms(10, protos)
```
Note that the labels and criticism_kernel are optional arguments which are None by default. If `criticism_kernel`
is none, then the prototype kernel will be used for criticisms. If labels are none, then returned labels will be None.
See more in the [examples](https://github.com/PhysBoom/mmd_critic/tree/main/examples)
## More Info
Read my [article](https://medium.com/@physboom/the-mmd-critic-method-explained-c6a77f2dbf18) for more info on the MMD critic method. I also encourage you to read the original [paper](https://papers.nips.cc/paper_files/paper/2016/hash/5680522b8e2bb01943234bce7bf84534-Abstract.html).
## Acknowledgements
The implementation here is based on Been Kim's [original implementation](https://github.com/BeenKim/MMD-critic/tree/master) and [paper](https://papers.nips.cc/paper_files/paper/2016/hash/5680522b8e2bb01943234bce7bf84534-Abstract.html)
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"description": "# mmd-critic\r\n\r\n[](https://github.com/yourusername/mmd-critic/blob/main/LICENSE)\r\n\r\nA Python package for implementing the Maximum Mean Discrepancy Critic (MMD-Critic) method. This method is commonly used to find prototypes and criticisms (outliers, roughly speaking) in datasets.\r\n\r\n## Installation\r\n\r\nYou can install the package via pip:\r\n\r\n```bash\r\npip install mmd-critic\r\n```\r\n\r\n## Usage\r\n\r\n```python\r\nfrom mmd_critic import MMDCritic\r\nfrom mmd_critic.kernels import RBFKernel\r\n\r\ncritic = MMDCritic(X, RBFKernel(sigma=1), criticism_kernel=RBFKernel(2), labels=y)\r\n\r\nprotos, proto_labels = critic.select_prototypes(50)\r\ncriticisms, criticism_labels = critic.select_criticisms(10, protos)\r\n```\r\n\r\nNote that the labels and criticism_kernel are optional arguments which are None by default. If `criticism_kernel`\r\nis none, then the prototype kernel will be used for criticisms. If labels are none, then returned labels will be None.\r\n\r\nSee more in the [examples](https://github.com/PhysBoom/mmd_critic/tree/main/examples)\r\n\r\n## More Info\r\n\r\nRead my [article](https://medium.com/@physboom/the-mmd-critic-method-explained-c6a77f2dbf18) for more info on the MMD critic method. I also encourage you to read the original [paper](https://papers.nips.cc/paper_files/paper/2016/hash/5680522b8e2bb01943234bce7bf84534-Abstract.html).\r\n\r\n## Acknowledgements\r\n\r\nThe implementation here is based on Been Kim's [original implementation](https://github.com/BeenKim/MMD-critic/tree/master) and [paper](https://papers.nips.cc/paper_files/paper/2016/hash/5680522b8e2bb01943234bce7bf84534-Abstract.html)\r\n",
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