Importance extraction based on Markov Chain Monte Carlo methods (IE-MCMC)
Python >= 3.7
numpy >= 1.16.2
scikit-learn >= 0.20.3
emcee >= 2.2.1
matplotlib >= 2.2.3
Download or clone the github repository, e.g. git clone https://github.com/rtmr/IE-MCMC
nwalkers: int (Number of walkers in MCMC sampling)
nstep: int (Number of step in MCMC sampling)
Temp: real (The value of T in probability distribuion)
Target dataset is set to the features with label information (last row). (Target.csv contains the proof stress depending on temper designations and composition elements in the 5000 series aluminum alloys.)
python IE-MCMC.py
This project is licensed under the terms of the MIT license.