Question 8: Wine Data – Prediction (8a) 6 pts – Using model3…
Question 8: Wine Data – Prediction (8a) 6 pts – Using model3, all_subsets_model, stepwise_model, and ridge_model, give a binary classification to each of the rows in wine_data_test, with 1 indicating a good quality wine. Use 0.5 as your classification threshold. (8b) 4.5 pts – For each model, display its accuracy, sensitivity, and specificity metrics. Hint: confusionMatrix() from the caret package could be used to calculate these metrics. (9b.1) Which model has the largest accuracy? (9b.2) Which model has the largest sensitivity?(9b.3) Which model has the largest specificity? (8c) 1 pt – In this context, should sensitivity or specificity matter more? Explain. Hint: Remember that sensitivity is the proportion of all 1s in the test set that are correctly classified as 1s, while specificity is the proportion of all 0s in the test set that are correctly classified as 0s. (8d) 1 pt – Based on 8b and 8c, which model performed the best?
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