We're training a binary perceptron model. At time t, a positive example (xi, Yi) was selected...

   

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We're training a binary perceptron model. At time t, a positive example (xi, Yi) was selected and the update rule was applied to get the new weight vector w(t) and the new bias b(t). At time t + 1, the example selected is exactly the same as (xi, Yi). Which of the following statements are true: Hint: to answer this question, it is helpful to write down the equation used to make the prediction at timet + 1 and to use the perceptron update rule to rewrite it as a function of parameters at time t. (w(t+1), 6(t+1)) will predict the correct class Yi (w(t+1), 6(t+)) will predict an incorrect class y' Y for Xi + f(t) w . None of the above. X + f(t+1) for Xi We're training a binary perceptron model. At time t, a positive example (xi, Yi) was selected and the update rule was applied to get the new weight vector w(t) and the new bias b(t). At time t + 1, the example selected is exactly the same as (xi, Yi). Which of the following statements are true: Hint: to answer this question, it is helpful to write down the equation used to make the prediction at timet + 1 and to use the perceptron update rule to rewrite it as a function of parameters at time t. (w(t+1), 6(t+1)) will predict the correct class Yi (w(t+1), 6(t+)) will predict an incorrect class y' Y for Xi + f(t) w . None of the above. X + f(t+1) for Xi

Answer rating: 100% (QA)

C wt Xi bt wt1 Xi bt1 Explanationfor step1 When training a binary perceptron model at each time step ... View the full answer