A local financial institution is re-assessing the approval process for their Emerald credit card. You have been asked to run a preliminary test on a 6-nearest neighbours algorithm using the data provided below. The available data includes clients' incomes (X1), credit scores (X2), family sizes (X3), and whether the client is in good standing (Y=1) or not(Y=0). If a customer is not in good standing, it means they have missed credit card payments. Data: Download CSV a. With the X variables being on different scales, you must first standardize the X data. Round all standardized values to two decimal places. What are the standardized values for client \#66 with an income of $81.7 thousand, a credit score of 712 , and a family size of 2 ? Using the rounded standardized data, perform one iteration of the leave-one-out nethod for the 6-nearest neighbours algorithm using client \#66 as the test point and the remaining data as the training set. i. What is the distance value for the 6th nearest neighbour? Express your answer rounded to four decimal places. Distance = ii. What is the predicted class for this test point? If there is a tie, use a randomized value of 0.292 to break the tie. Predicted Class = The results of the entire leave-one-out method can be found below. Use these results to fill in the confusion matrix below. Results: Download CSV What is the overall error rate and accuracy of this 6-nearest neighbours algorithm? Express your answers as percentages rounded to two decimal places. A local financial institution is re-assessing the approval process for their Emerald credit card. You have been asked to run a preliminary test on a 6-nearest neighbours algorithm using the data provided below. The available data includes clients' incomes (X1), credit scores (X2), family sizes (X3), and whether the client is in good standing (Y=1) or not(Y=0). If a customer is not in good standing, it means they have missed credit card payments. Data: Download CSV a. With the X variables being on different scales, you must first standardize the X data. Round all standardized values to two decimal places. What are the standardized values for client \#66 with an income of $81.7 thousand, a credit score of 712 , and a family size of 2 ? Using the rounded standardized data, perform one iteration of the leave-one-out nethod for the 6-nearest neighbours algorithm using client \#66 as the test point and the remaining data as the training set. i. What is the distance value for the 6th nearest neighbour? Express your answer rounded to four decimal places. Distance = ii. What is the predicted class for this test point? If there is a tie, use a randomized value of 0.292 to break the tie. Predicted Class = The results of the entire leave-one-out method can be found below. Use these results to fill in the confusion matrix below. Results: Download CSV What is the overall error rate and accuracy of this 6-nearest neighbours algorithm? Express your answers as percentages rounded to two decimal places