Install the library TH.data. Use the data named GlaucomaM in this library. The GlaucomaM data has 196 observations in two classes. 62 variables are derived from a confocal laser scanning image of the optic nerve head, describing its morphology. Observations are from normal and glaucomatous eyes, respectively. Use the help file to know more about the dataset. Your goal is to predict whether a person will have glaucoma based on the 62 variables. Identify the predictors and the response variables in the dataset. Randomly select 70% of the data as training data and the remaining 30% as test data. Install the package glmnet and use elastic net method on the training data to determine an appropriate model. Then use this model to do predictions on the test dataset. Report which covariates were selected in the model. You do not need to interpret any coefficient estimate. Prediction and variable selection are the main focus of your analysis.