Final Project for Bayesian Machine Learning
Leveraging Bayesian methods to understand how certain climatic measures contribute to the start of wildfires, how these base measures compare to the government-sanctioned Fire Weather Index, and the uncertainty surrounding general predictions of forest fires in two distinct regions in northern Algeria.
Code Instructions
To run the code for this assignment, use the jupyter notebook attached in this repository- AlgeriaFiresProject_Report.ipynb
In order for the code to work, you will need to download this dataset from the UCI Machine Learning Repository and add it to the same directory as your jupyter notebook.
Additionally, here is the list of libraries and versions that you will need to have installed for the code to function properly:
arviz 0.15.1
matplotlib 3.7.1
sklearn 1.2.2
numpy 1.23.5
pymc 5.7.2
scipy 1.11.4
pandas 1.5.3
seaborn 0.12.2