Power Factor Prediction of Thermoelectric Materials Using Machine Learning

Premise

This is a random forest machine learning model for power pactor prediction of thermoelectric materials.

Developed in 2022.4-2 at
School of Mechanical Engineering
Guizhou University, Guiyang, China

Environment Setup

To use this machine learning model, you need to create an environment with the correct dependencies. Using Anaconda this can be accomplished with the following commands:

conda create --name PF_predict python=3.6
conda activate PF_predict
conda install --channel conda-forge pymatgen
pip install matminer
pip install scikit-learn==0.24.1

Setup

Once you have setup an environment with the correct dependencies you can install by the following commands:

conda activate PF_predict
git clone https://github.com/Yuxinya/PF_predict
cd PF_predict
pip install -e .

Example Use

In order to test your installation you can run the following example from your PF_predict directory:

cd /path/to/PF_predict/
python predict.py -i formula 

for example:
python predict.py -i Al16O24