One vs. Rest SVM 5/5 points (graded) Use the sklearn package and build the SVM model...

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One vs. Rest SVM 5/5 points (graded) Use the sklearn package and build the SVM model on your local machine. Use random_state = 0, values for other parameters. Available Functions: You have access to the sklearn's implementation of the linear SVM as LinearSVC; No need to import anything. 4 5 6 7 8 9 10 11 12 13 clf.fit(train_x, train_y) 14 pred_test_y= clf.predict(test_x) 15 return pred_test_y 16 17 18 Press ESC then TAB or click outside of the code editor to exit Args: train_x - (n, d) NumPy array (n datapoints each with d features) train_y - (n, ) NumPy array containing the labels (0 or 1) for each training data point test_x (m, d) NumPy array (m datapoints each with d features) pred_test_y - (m,) NumPy array containing the labels (0 or 1) for each test data point clf = LinearSVC(random_state=0, C=0.1) Returns: 0, C=0.1 and default raise NotImplementedError Correct Binary classification error 0/5 points (graded) Report the test error by running run_svm_one_vs_rest_on_MNIST. Error 1.0 Submit You have used 3 of 20 attempts Save One vs. Rest SVM 5/5 points (graded) Use the sklearn package and build the SVM model on your local machine. Use random_state = 0, values for other parameters. Available Functions: You have access to the sklearn's implementation of the linear SVM as LinearSVC; No need to import anything. 4 5 6 7 8 9 10 11 12 13 clf.fit(train_x, train_y) 14 pred_test_y= clf.predict(test_x) 15 return pred_test_y 16 17 18 Press ESC then TAB or click outside of the code editor to exit Args: train_x - (n, d) NumPy array (n datapoints each with d features) train_y - (n, ) NumPy array containing the labels (0 or 1) for each training data point test_x (m, d) NumPy array (m datapoints each with d features) pred_test_y - (m,) NumPy array containing the labels (0 or 1) for each test data point clf = LinearSVC(random_state=0, C=0.1) Returns: 0, C=0.1 and default raise NotImplementedError Correct Binary classification error 0/5 points (graded) Report the test error by running run_svm_one_vs_rest_on_MNIST. Error 1.0 Submit You have used 3 of 20 attempts Save

Answer rating: 100% (QA)

To build a One vs Rest SVM model using the sklearn package you can use the Line... View the full answer