Questiоn 7: Wine Dаtа - Regulаrized Regressiоn (7a) Using wine_data_train, cоnduct ridge regression with quality as the binary response variable and all other variables in wine_data_train as the predicting variables. (7a.1) 3 pts - Use 10-fold cross validation on the misclassification error to select the optimal lambda value. What optimal lambda value did you obtain? Hint: Make sure to change the value of type.measure in order to perform cross validation on the misclassification error. If needed, you can take a look at the help file by typing ?cv.glmnet. (7a.2) 1.5 pts - Fit a glmnet object with nlambda = 100. Call it ridge_model. (7a.3) 1 pt - Display the estimated coefficients at the optimal lambda value.
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