This project is how I build a Machine Learning model which is used for analysing the cause of certain error in a database. The model is based on Decision Tree and Random Forest. This is just a simple classification model that is used to classify if a certain set of data belong to certain error label.
This project is using this following python library:
- Pandas
- Numpy
- Matplotlib
- Seaborn
- Scikit Learn
The performance of the model is measured as an accuracy score. The accuracy score for both model is stated below:
- Decision Tree accuracy 0.79
- Random Forest accuracy 0.81