Continuing on the biopsy dataset.

Questions

• Create a vector glm.pred that contains the predicted values the glm.fit model you created previously in Logistic Regression 3 (use a cut-off point of 0.5, with “malignant” corresponding to 1, and “benign” to 0)
• Create a table that compares the predicted results with the actual diagnosis and store it in glm.table
• Calculate the accuracy of the model and store in glm.acc

Note: class is a protected keyword in R. If you want to refer to the class column of the biopsy dataset, please explicitly mention biopsy$class. If you create the glm.pred vector, make sure you pass the correct size. You can easily find this with the nrow(biopsy) command. Make sure that you have omitted the NA values like we did in Logistic Regression 3¹

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Assume that:

• The MASS library has been loaded
• The biopsy dataset has been loaded and attached
• The rows with NA values have been dropped
• The ID column has been dropped
• The model glm.fit created in Logistic Regression 3² is already loaded