Credit Card Use: Consider the following hypothetical bank data on consumers’ use of credit card credit facilities in Table 11.3. Create a JMP data table using Table 11.3 (File>New>Data Table), and create a neural network model (Analyze>Predictive Modelling>Neural) using your new data table. Use the default validation method (Holdback Portion) and use the random seed 123. (see the screen capture below) TABLE 11.3 Data for Credit Card Example and Variable Descriptions Years Salary Used Credit 43 65 4 18 1 3 15 6 53 95 88 112 0 What is the misclassification rate on the validation set? [ Select ] ["0", "0.4268", "0.012", "0.4"] How many parameters are estimated to build this model? [ Select ] ["14", "15", "13", "12"] (Hint: use the red triangle option "Show Estimates") Use
Credit Card Use: Consider the following hypothetical bank data on consumers’ use of credit card credit facilities in Table 11.3. Create a JMP data table using Table 11.3 (File>New>Data Table), and create a neural network model (Analyze>Predictive Modelling>Neural) using your new data table. Use the default validation method (Holdback Portion) and use the random seed 123. (see the screen capture below) TABLE 11.3 Data for Credit Card Example and Variable Descriptions Years Salary Used Credit 43 65 4 18 1 3 15 6 53 95 88 112 0 What is the misclassification rate on the validation set? [ Select ] ["0", "0.4268", "0.012", "0.4"] How many parameters are estimated to build this model? [ Select ] ["14", "15", "13", "12"] (Hint: use the red triangle option "Show Estimates") Use the Profiler (red triangle option) to explore how the predicted response changes as you change values of the predictors. Describe what you observe. Determine whether the statement below is either true or false. As years increases, the
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