AI Midterm Lab Quiz 2_ Attempt review

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Started on Saturday, 8 June 2024, 7:02 AM State Finished Completed on Saturday, 8 June 2024, 7:20 AM Time taken 17 mins 29 secs Marks 16.00/20.00 Grade 80.00 out of 100.00 Question 1 Correct Mark 1.00 out of 1.00 Question 2 Correct Mark 1.00 out of 1.00 Question 3 Correct Mark 1.00 out of 1.00 What is the "M" step in the EM algorithm? a. The step where the expectation of the latent variables is calculated b. The step where the prediction accuracy of the model is calculated c. The step where the model parameters are updated ✓ d. The step where the likelihood of the model is maximized What is the main advantage of the Hebb rule? a. It is fast to converge ✓ b. It is able to handle nonlinear relationships c. It is easy to implement d. It is able to handle large datasets What is the Hebb rule? a. A rule used to calculate the output of a neural network b. A rule used to adjust the weights in a neural network ✓ c. A rule used to determine the structure of a neural network d. A rule used to determine the input to a neural network  08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 1/6

Question 4 Correct Mark 1.00 out of 1.00 Question 5 Correct Mark 1.00 out of 1.00 Question 6 Correct Mark 1.00 out of 1.00 Question 7 Incorrect Mark 0.00 out of 1.00 What is the EM algorithm used to estimate in the "E" step? a. The prediction accuracy of the model b. The latent variables ✓ c. The model parameters d. The likelihood of the model What is the Naive Bayes classifier used for? a. To predict the value of a continuous variable b. To classify data into different categories based on certain features ✓ c. To predict the probability of an event occurring d. All of the above What is the equation for the Hebb rule? a. w(new) = w(old) + η(output - target)x(input) b. w(new) = w(old) + η(target - output)x(input) c. w(new) = w(old) + η(input - output)x(target) d. w(new) = w(old) + η(output)x(input) ✓ What is the advantage of using the Gaussian Naive Bayes classifier over other types of Naive Bayes classifiers? a. It is more accurate b. It is able to handle categorical features × c. It is able to handle continuous features d. It is faster to train and predict 08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 2/6

Question 8 Correct Mark 1.00 out of 1.00 Question 9 Correct Mark 1.00 out of 1.00 Question 10 Incorrect Mark 0.00 out of 1.00 Question 11 Correct Mark 1.00 out of 1.00 What is the advantage of the Naive Bayes classifier over other classifiers? a. It is faster to train and predict ✓ b. It is more flexible c. It is more accurate d. It is able to handle large amounts of data What is the EM algorithm used to optimize in the "M" step? a. The likelihood of the model ✓ b. The prediction accuracy of the model c. The model parameters d. The latent variables What is the disadvantage of the Naive Bayes classifier? a. It is slower to train and predict b. It is less accurate c. It is inflexible d. It is unable to handle large amounts of data × What is the learning rule for a perceptron called? a. The Hebbian Rule ✓ b. The Perceptron Learning Algorithm c. The Backpropagation Algorithm d. The Delta Rule 08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 3/6

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Question 12 Correct Mark 1.00 out of 1.00 Question 13 Correct Mark 1.00 out of 1.00 Question 14 Correct Mark 1.00 out of 1.00 Question 15 Incorrect Mark 0.00 out of 1.00 What is the Kullback-Leibler (KL) distance used for? a. To measure the similarity between two probability distributions b. To measure the predictability of a probability distribution c. To measure the dissimilarity between two probability distributions ✓ d. To measure the uncertainty of a probability distribution What is the EM algorithm used for? a. Classification b. All of the above ✓ c. Clustering d. Regression What is the main goal of the EM algorithm? a. To maximize the prediction accuracy of the model b. To maximize the likelihood of a model given the data ✓ c. To minimize the error between the predicted and actual values of the data d. To minimize the cost or loss function of a model What is the main advantage of using a directed acyclic graph (DAG) over other types of graphs? a. DAGs can represent more complex relationships between data b. DAGs are easier to understand and visualize c. DAGs are more efficient for storing and processing data d. All of the above × 08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 4/6

Question 16 Correct Mark 1.00 out of 1.00 Question 17 Correct Mark 1.00 out of 1.00 Question 18 Correct Mark 1.00 out of 1.00 Question 19 Incorrect Mark 0.00 out of 1.00 What is the assumption made by the Naive Bayes classifier? a. That the features in the data are dependent on each other b. That the features in the data are normally distributed c. That the features in the data are independent of each other ✓ d. That the features in the data are uniformly distributed What is the least squares method used for? a. To calculate the variance of a data set b. To calculate the mean of a data set c. To solve systems of linear equations d. To find the line of best fit for a set of data ✓ What is the main disadvantage of the Hebb rule? a. It is slow to converge b. It is unable to handle large datasets c. It is unable to handle nonlinear relationships ✓ d. It is prone to overfitting What is the "E" step in the EM algorithm? a. The step where the prediction accuracy of the model is calculated b. The step where the expectation of the latent variables is calculated c. The step where the likelihood of the model is maximized d. The step where the model parameters are updated × 08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 5/6

Question 20 Correct Mark 1.00 out of 1.00 What is supervised learning used for? a. Unsupervised learning tasks b. Regression tasks c. Both classification and regression tasks ✓ d. Classification tasks ◄ Midterm Quiz 2 Jump to... Module 9 ► 08/06/2024, 10:20 Midterm Lab Quiz 2: Attempt review https://trimestral.amaesonline.com/2333/mod/quiz/review.php?attempt=117976&cmid=64470 6/6

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