Author: @pathananas2007
End-to-end Rainfall Prediction pipeline using Python. Implements data cleaning, feature engineering (Season), preprocessing, and multiple ML models (Random Forest, XGBoost, SVM, KNN, Logistic Regression, Gradient Boosting) with hyperparameter tuning, evaluation, and model comparison.
- File:
data final.csv - Source: Australian Government Bureau of Meteorology – Climate Data Online
- Contains cleaned weather data for Melbourne, Melbourne Airport, and Watsonia.
This project is tested with Python 3.11.
All required libraries are listed in requirements.txt. Key packages:
- pandas
- numpy
- scikit-learn
- xgboost
- matplotlib
- seaborn
)
Install dependencies with:
pip install -r requirements.txt