9. (30 points) create a classifier to classify each observation to two class, Benign and Malignant: Target: Benign or Malignant - train/test size: 80:20 - random_state=1 features columns X : "radius_mean","texture_mean","perimeter_mean","area_mean","smoothness_mean","compac tness_mean" answer the following questions: 1. print out the shape of X,y,X_train, X_test, Y_train,Y_test 2. report Logistic Regression accuracy of X,Y 3. report KNN accuracy of X,Y when k=5 4. loop k1-k25 and plot KNN accuracy of X,Y sample of k1-k25 plot of X (your chart might look different!) 0.94 0.93 0.91 0.90 0.89- 5 10 15 20 25 Value of K for KNN of X