4. You are given the count matrix in the table below for the attribute "Previous GPA". The class label is whether a student will pass(C1) or fail(CO) a class. We want to use the attribute "Previous GPA" as our splitting attribute in an inner node of a decision tree with a binary test condition. Which is the best way to partition the attribute values into two groups? Form the count matrices for the different partitions and compute the classification error. Explain your reasoning while considering the metric of classification error to evaluate the different partitions. Previous GPA Bad Fair Good Very good pass(C1) 6 9. 3 fail(CO) 4 4.

A decision tree is a unique kind of probability tree. A popular and powerful tool used for prediction and classification. The decision tree structure is the same as a flowchart with a tree structure. The internal node refers to the attribute test, the br…