(5pts) Feature Selection & Preprocessing A friend asks you for some help with a feature selection project. Your friend goes out and collects data, D, for their project. Using D, your friend tries many subsets FCA by adapting F based on the error of a classifier. They return F that corresponds to the smallest classification error. After they have the feature set F they perform randomized trials to estimate the accuracy of the model using their feature selector This is the procedure they carry out to validate the impact of the feature selection routine This procedure is repeated . Make a new data set D with F features using the feature selection routine . Repeat 50 times Split D, into randomized training & testing sets (80/20% splits) - Train a classifier and record its error . Report the error averaged over 50 trials Critique and respond to how your friend performed their analysis