ImmoEliza-Regression

Introduction | Description | Usage | Timeline | List of Improvements

Introduction

1. Data cleaning
2. Features engineering
3. Data formatting
4. Model preselected - XGBoost
5. Applying the model
6. Model evaluation

Description

Packages used:

• pandas
• numpy
• xgboost
• matplotlib
• seaborn
• sklearn
• shap

Info on model performance can be found in eval_metrics.md

Usage

Everything runs from main.py, the 3 data sets are needed for the program to work.

Timeline

2 Dec 2024 - project phase initiated at BeCode Brussels AI & Data Science Bootcamp

9 Dec 2024 - project phase (Machine Learning) ended

List of Improvements

• Front-end
• Performance
• Code comments