Question 7 [2 pts]: A classifier is trained from a given training set, and is validated on a test set with 10 instances. The results generated from the classifier is shown in the following table, where the first column is the index of the test instances, the $2^{\text {nd }}$ column denotes the predicted probability of the test instance belonging to class "1" (there are only two classes: "1" and "0"), and the third column denotes the true label of the test instance. Using decision rule: a test instance is classified as "1" if its predicted probability belonging to class " 1 " is greater or equal to $0.5$, and "0" otherwise. - Please report the confusion matrix of the classifier [ $0.5 \mathrm{pt}$ ]. - Please report the classification accuracy [0.5 pt], True Positive Rate (0.5 pt], and False Positive Rates $[0.5 \mathrm{pt}]$ of the classifier (assuming " 1 " is the positive). \begin{tabular}{|ccc|} Index & Predicted probablitly belonging to 1 & True Label & 1 & $0.8$ & 1 W \hline 2 & $0.2$ & 0W \hline 3 & $0.4$ & 1 W \hline 4 & $0.55$ & 1 W \hline 5 & $0.45$ & 1 6 & $0.9$ & 1 \hline 7 & $0.3$ & 0W \hline 8 & $0.4$ & 0 \hline 9 & $0.56$ & 1 10 & $0.92$ & 1 W \hline \end{tabular CS.VS. 1165