Hi, I need help for this question: Compute the slack i associated with the misclassified points.

I had make a few attempt for different code, but after submission the result shown the answer isn't correct. My code as below:

# your code here import numpy as np from sklearn.svm import SVC # your code here clf = SVC(C=1.0, kernel='linear') clf.fit(X, y) #Get the predictions predictions = clf.predict(X) #Get the dual coefficients and bias dual_coef = clf.dual_coef_[0] bias = clf.intercept_[0] #Initialize a list for the slacks slacks = [] for i, example in enumerate(X): if predictions[i] != y[i]: # Compute the slack for misclassified examples slack = 1 - y[i] * (np.dot(example, clf.coef_.T) + bias) slacks.append(slack.item()) print(slacks)

The error for first attempt after submission:

--------------------------------------------------------------------------- NameError Traceback (most recent call last)  in  32 # compute the slack associated with the misclassified points 33 # return a list slacks with the slack computations ---> 34 slacks = [slack1, slack2] 35 slack1 = 1.8333333333333355 36 slack2 = 1.666666666666668

Error for second attempt for submission:

--------------------------------------------------------------------------- AssertionError Traceback (most recent call last)  in  Traceback Redacted AssertionError: Check Part 1D. Look at slacks.

Please help me on the code. Thank you so much.