3. Support Vector Machine Bookmark the Project due Mar 17, 2021 01:59 EET Bob thinks it is cleatly not a regression problem but a classification problem. He thinks that we can change it into a binary classification and use the support vector machine we leamed in Lecture 4 to solve the problem. In order to do so, he suggests that we can build an one vs. test model for every digit. For example, classifying the digits into two classes: 0 and not 0. Bob wrote a function run_sva_one_vs_rest on MNIST where he changed the labels of digits 1-9 to land keeps the label for digit 0. He also found that sklearn package contains an svi nodel that you can use directly. He gave you the link to this model and hope you can tell him how to use that You will be working in the file parti/svm.py in this problem important. For this problem, you will need to use the sulkil-lear library. If you don't have it, installit using pip instsil sklearn One vs. Rest SVM 50/50 pomegraded Use the skleara package and build the SVM model on your local machine. Use random state - 8. 4-8.1 and delault YUUES Tor other paneles geable Function You have access to the skleansimplementation of the meat SVM35 litersvo -No need to import me ys est vtral, train y test Cineansverande status. 1) Edulcordato pred test clf.predict(test En pred te THE NOSError Press Esd then TAB OF Ek outside of tuode editor o ex Correct Test results Ses full output CORRECT See full oullut Submit You have used of 25 attempts Savo Binary classification error 0.0/5.0 points (graded) Report the test error by running run svart MNIST Error