dhruvramani / C2ae Multilabel Classification
Tensorflow implementation for the paper 'Learning Deep Latent Spaces for Multi-Label Classfications' in AAAI 2017
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C2AE
This is the Tensorflow implementation for the paper 'Learning Deep Latent Spaces for Multi-Label Classfications' published in AAAI 2017.
Installation
The model was built and tested using Python 3! Install the following dependencies :
pip3 install liac-arff
Running
This code supports the .arff data format, however if you wish to use any other data format, convert it into numpy arrays and dump it to the data/dataset_name with the name format as mentioned in data/README.md and modify model/src/parser.py.
cd ./model/src
python3 __main__.py
Logs
All the logs are saved in ./model/stdout and you can visualize the loss using tensorboard by pointing it to ./model/results/tensorboard.
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