In this project I build a program that implement a decision tree from categorical attributes and two-class classification tasks. The programming part requires building a tree from a training dataset and classifying unseen instances.
The dataset comes from a risk loan dataset, which is being used to predict the risk quality of a loan application. Each instance is classified as good (class G) or bad(class B).