https://github.com/alexcoca/hi-vae

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Host: GitHub
Owner: alexcoca
License: mit
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Fork of probabilistic-learning/HI-VAE

Created almost 6 years ago · Last pushed about 6 years ago

https://github.com/alexcoca/HI-VAE/blob/master/

# HI-VAE

This repository contains the implementation of our Heterogeneous Incomplete Variational Autoendoder model (HI-VAE). It has been written in Python, using Tensorflow.

The details of this model are included in this [paper](https://arxiv.org/abs/1807.03653). Please cite it if you use this code for your own research.

## Databse description

There are three different datasets considered in the experiments (Wine, Adult and Default Credit). Each dataset has each own folder, containing:

* **data.csv**: the dataset
* **data_types.csv**: a csv containing the types of that particular dataset. Every line is a different attribute containing three paramenters:
* type: real, pos (positive), cat (categorical), ord (ordinal), count
* dim: dimension of the variable
* nclass: number of categories (for cat and ord)
* **Missingxx_y.csv**: a csv containing the positions of the different missing values in the data. Each "y" mask was generated randomly, containing a "xx" % of missing values.

You can add your own datasets as long as they follow this structure.

## Files description

* **script_HIVAE.sh**: A script with a simple example on how to run the models.
* **main_scripts.py**: Contains the main code for the HIVAE models.
* **loglik_ models_ missing_normalize.py**: In this file, the different likelihood models for the different types of variables considered (real, positive, count, categorical and ordinal) are included.
* **model_ HIVAE_inputDropout.py**: Contains the HI-VAE with input dropout encoder model.
* **model_ HIVAE_factorized.py**: Contains the HI-VAE with factorized encoder model

## Contact

**Alfredo Nazabal**: anazabal@turing.ac.uk

# Code Pre-requisites

First,
```console
$ git clone https://github.com/amirhk/mace.git
$ pip install virtualenv
$ cd mace
$ virtualenv -p python3 _venv
$ source _venv/bin/activate
$ pip install -r pip_requirements.txt
$ chmod +x script_HIVAE.sh
```

Then, run
```console
$ ./script_HIVAE.sh
```

Owner

Name: Alexandru Coca
Login: alexcoca
Kind: user
Location: Cambridge
Company: University of Cambridge

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