Rain Prediction Binning Model
An applied machine learning project that forecasts rainfall using historical data and statistical binning techniques.
This project combines KNIME and Python to evaluate several machine learning methods, then determine the best approach based on experimental results and performance testing.
- Tools: KNIME, Python, pandas, scikit-learn
- Approach: compare multiple ML methods and select the best-performing model
- Focus: statistical binning, feature engineering, and model validation
- Results: achieved strong accuracy and practical prediction performance
- Outcome: evidence-based selection of the optimal rainfall prediction workflow