The goal is to build a decision tree that, based on the other features in the set, predicts

whether or not a patient has malignant cancer. So this is a classification problem. Using

tree.DecisionTreeClassifier and other functions in the scikit$-$learn library, one can build

a decision tree and calculate both its training accuracy when fitted to the entire data set as

well as its accuracy using $10-$fold cross validation $($which gives a better idea of true accuracy$).$

In this question you will need to complete two sub$-$components: