📗 The quizzes must be completed during the lectures and submitted on TopHat: Link. No Canvas submissions are required. The grades will be updated by the end of the week on Canvas.
📗 Please submit a regrade request if (i) you missed a few questions because you are late or have to leave during the lecture; (ii) you selected obviously incorrect answers by mistake (one or two of these shouldn't affect your grade): Link
The following questions may appear as quiz questions during the lecture. If the questions are not generated correctly, try refresh the page using the button at the top left corner.
📗 [1 points] There will be around 10 new questions on the exam. I will post \(n\) of them before the exam (tonight):
📗 A: \(n = 0\).
📗 B: \(n = 1\) if more than percent of you choose B.
📗 C: \(n = 2\) if more than percent of you choose C.
📗 D: \(n = 3\) if more than percent of you choose D.
📗 E: \(n = 0\).
📗 Answer: .
📗 [3 points] Given the following Bayesian network and the training set, what is the MLE estimate of \(\mathbb{P}\){|} without smoothing?
\(A\)
\(B\)
\(C\)
\(D\)
\(E\)
📗 Answer: .
📗 [3 points] Given the following Bayesian network and the estimated CPTs (conditional probability table), and a new data point with = , = , what is estimated probability of = ?
\(\hat{\mathbb{P}}\left\{A\right\}\)
\(\hat{\mathbb{P}}\left\{B\right\}\)
\(\hat{\mathbb{P}}\left\{C | A, B\right\}\)
\(\hat{\mathbb{P}}\left\{C | A, \neg B\right\}\)
\(\hat{\mathbb{P}}\left\{C | \neg A, B\right\}\)
\(\hat{\mathbb{P}}\left\{C | \neg A, \neg B\right\}\)