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Devashish13 authored Nov 25, 2024
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# RAISING

This repository contains the source code, simulation data, and documentation for the **RAISING**, a two-stage neural network(NN) implementation framework that first performs hyperparameter tuning to devise the best NN architecture and then performs training on the entire data to estimate the feature importance. The method has been published in Nucleic Acids Research (<https://doi.org/10.1093/nar/gkae1027>).
This repository contains the source code, simulation data, and documentation for the **RAISING**, a two-stage neural network(NN) implementation framework that first performs hyperparameter tuning to devise the best NN architecture and then performs training on the entire data to estimate the feature importance. The method has been published in Nucleic Acids Research (<https://doi.org/10.1093/nar/gkae1027>). The source code is available on GitHub(<https://github.com/Devashish13/RAISING/>)

## RAISING installation

Expand All @@ -10,8 +10,12 @@ Create a conda environment to install the RAISING
conda create -n RAISING_env python=3.9
conda activate RAISING_env
```
Install the package through pypi
```
pip install RAISING
```

Install the package through a github repository
Install the package through the github repository

```
pip install git+https://github.com/Devashish13/RAISING.git
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