This project is a machine learning model that predicts daily rainfall using various algorithms, including Decision Tree Classifier, Support Vector Machine, Multilayer Neural Network, Naive Bayes, Logistic Regression, and Ensemble Classifier. The project aims to provide accurate weather predictions by analyzing historical weather data.
To see the details of the project, including data preprocessing, model training, and evaluation, please view the .ipynb notebook provided in this repository. The notebook contains all the necessary code and explanations.
- Decision Tree Classifier
- Support Vector Machine
- Multilayer Neural Network
- Naive Bayes
- Logistic Regression
- Ensemble Classifier
The Multilayer Neural Network and XGBoost models showed the highest accuracy in predicting rainfall.
- Python
- Jupyter Notebook