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@ -1,5 +1,4 @@
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## Introduction
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## Introduction
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---
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This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques
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This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques
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@ -7,12 +6,11 @@ This package is designed to generate synthetic data from a dataset from an origi
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- With "Earth mover's distance"
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- With "Earth mover's distance"
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## Installation
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## Installation
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---
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pip install git+https://hiplab.mc.vanderbilt.edu/git/aou/data-maker.git@release
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pip install git+https://hiplab.mc.vanderbilt.edu/git/aou/data-maker.git@release
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## Usage
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## Usage
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---
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After installing the easiest way to get started is as follows (using pandas). The process is as follows:
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After installing the easiest way to get started is as follows (using pandas). The process is as follows:
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1. Train the GAN on the original/raw dataset
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1. Train the GAN on the original/raw dataset
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@ -35,7 +33,6 @@ After installing the easiest way to get started is as follows (using pandas). Th
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## Limitations
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## Limitations
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---
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GANS will generate data assuming the original data has all the value space needed:
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GANS will generate data assuming the original data has all the value space needed:
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@ -49,7 +46,6 @@ GANS will generate data assuming the original data has all the value space neede
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e.g:measurements (height, blood pressure, ...)
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e.g:measurements (height, blood pressure, ...)
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## Credits :
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## Credits :
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---
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- [Ziqi Zhang](ziqi.zhang@vanderbilt.edu)
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- [Ziqi Zhang](ziqi.zhang@vanderbilt.edu)
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- [Brad Malin](b.malin@vanderbilt.edu)
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- [Brad Malin](b.malin@vanderbilt.edu)
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