Metadata-Version: 2.1
Name: kfda
Version: 0.1.0
Summary: Kernel FDA implementation described in https://arxiv.org/abs/1906.09436
Home-page: https://github.com/concavegit/kfda
Author: Kawin Nikomborirak
Author-email: concavemail@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# Kernel FDA
This repository implements Kernel FDA as described in [https://arxiv.org/abs/1906.09436](https://arxiv.org/abs/1906.09436).

## Examples
See [`examples`](examples) for examples.

After running them, you can plug corresponding pairs of generated
`*embeddings.tsv` and `*labels.tsv` into Tensorflow's
[Embedding Projector](https://projector.tensorflow.org/)
to visualize the embeddings.
For example, running `mnist.py` and then loading
`mnist_test_embeddings.tsv` and `mnist_test_labels.tsv` shows the
following using the UMAP visualizer:

![MNIST Kernel FDA embeddings](https://github.com/concavegit/kfda/blob/master/img/mnist.png?raw=true)

## Notebook
Alternatively, see the
[Colab Notebook](https://colab.research.google.com/drive/1nnVphyZ_0QKYZbmdJaIBjm-zYO4xwF0b#scrollTo=6Pfpr7DDQota).


