This project is about rain prediction using 2 machine learning algorithms: Random Forest and Decision Tree Classifier. I was surprised to see the results of this project. Previously I had worked on this project with relatively low accuracy, which was around 75-80%. In addition, confusion matrix and classification report also produce low recall and precision values. But I do it again with different preprocessing data, it turns out the results change dramatically. But I doubt the results, so please correct if there is an error.
- Python
- Gathering
- Cleaning
- Exploration
- Preprocessing
- Modeling