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Framework to build, evaluate, select, and compare ML classification and regression models using high-dimensional biological data and other covariates

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ruppinlab/sklearn-bio-workflows

 
 

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sklearn-bio-workflows

Installation

Install and set up Mambaforge

Clone git repository and submodules:

git clone [email protected]:hermidalc/sklearn-bio-workflows.git
cd sklearn-bio-workflows
git submodule update --init --recursive

To install conda environment on Intel architecture hardware:

mamba env create -f envs/sklearn-bio-workflows-mkl.yml

Otherwise:

mamba env create -f envs/sklearn-bio-workflows.yml

Activate the environment:

mamba activate sklearn-bio-workflows

Install non-conda packages into environment:

./utils/install_nonconda_r_pkgs.R

Updates

Update the git repository and submodules:

git pull
git submodule update --recursive

To update the conda environment on Intel architecture hardware:

mamba env update -f envs/sklearn-bio-workflows-mkl.yml

Otherwise:

mamba env update -f envs/sklearn-bio-workflows.yml

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Framework to build, evaluate, select, and compare ML classification and regression models using high-dimensional biological data and other covariates

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  • Python 98.1%
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  • R 0.2%