How would I go at finding the Binned_X1 for a data set

5 Exercise 9-24 Algo (Using Analytic Solver) For Analytic Solver, partition data sets into 60% training and 40% validation and use 12345 as the default random seed. If the predictor variable values are in the character format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numerical variable. 0.75 points Skipped The accompanying data set contains three predictor variables (x1, x2, and x3) and the target variable ()). ExpictureClick here for the Excel Data File a. Bin predictor variables x1, x2, and x3. Choose the Equal count option and 3 bins for each of the three variables. What are the bin Book numbers for the variables of the first two observations? Binned_X1 Binned_X2 Binned_X3 Hint Observation 1 Observation 2 Print References b. Partition the data to develop a naive Bayes classification model where "1' denotes the positive or success class for y. Report the accuracy, specificity, sensitivity, and precision rates for the validation data set. (Enter your answers as decimals and round them to 2 decimal places.) Accuracy Specificity Sensitivity Precision5 c-1. Generate the ROC curve. What is the area under the ROC curve (or the AUC value)? (Round your answer to 4 decimal places.) AUC value of the ROC curve 0.75 points Skipped c-2. Is the following statement a true statement? eBook The ROC curve shows that the naive Bayes model performs better than the baseline model in terms sensitivity and specificity across all possible cutoff values. Hint O True O False Print References d. Change the cutoff value to 0.2. Report the accuracy, specificity, sensitivity, and precision rates for the validation data set. (Enter your answers as decimals and round them to 2 decimal places.) Accuracy Specificity Sensitivity Precision