In this project, I build a Random Forest Classifier model (with 10 decision-trees) to predict safety of the car. The accuracy increases with number of decision-trees. I have also demonstrated the feature selection process using the Random Forest model.
I have used the Car Evaluation Data Set from the UCI Machine Learning Repository website. Also, the dataset is provided in the repository.