Q102: Regression trees are often used to model ……….. data.
Q103: Which supervised learning method can handle both numerical and categorical input attributes?
(A) linear regression
(B) Bayes classifier
(C) logistic regression
(D) backpropagation learning
Q104: In language understanding, the levels of knowledge that does not include?
Q105: Which is the correct sequence of steps for gradient descent algorithm: (1). Calculate the difference between the actual and predicted values (2). Iterate until you discover the optimal network weights (3). Pass an input via the network to obtain values from the output layer (4). Set up the random weight and bias (5). Change the values of each neuron that contributes to the mistake to minimize the error.
(A) 1, 2, 3, 4, 5
(B) 5, 4, 3, 2, 1
(C) 3, 2, 1, 5, 4
(D) 4, 3, 1, 5, 2
Q106: You are evaluating papers for the World’s Fanciest Machine Learning Conference and come across the following submissions. Which ones would you be willing to accept?
(A) My method achieves a training error lower than all previous methods!
(B) My method achieves a test error lower than all previous methods! (Footnote: When regularization parameter λ is chosen so as to minimize test error.)
(C) My method achieves a test error lower than all previous methods! (Footnote: When regularization parameter λ is chosen so as to minimize cross-validation error.)
(D) My method achieves a cross-validation error lower than all previous methods! (Footnote: When regularization parameter λ is chosen so as to minimize cross-validation error.)
Q107: Let’s say you wish to divide a graph G into two subgraphs. Let L represent G’s Laplacian matrix. Which of the following might assist you in locating a suitable split?
(A) The eigenvector corresponding to the second largest eigenvalue of L
(B) The left singular vector corresponding to the second-largest singular value of L
(C) The eigenvector corresponding to the second smallest eigenvalue of L
(D) The left singular vector corresponding to the second-smallest singular value of L
Q108: It has been shown that there is a very clear association between math exam scores and the quantity of physical activity performed by a student on test day. What conclusions can you draw from this? (1). A strong correlation indicates that test scores are high following exercise. (2). Causation is not implied by correlation. (3). The strength of the linear association between the quantity of exercise and test results is measured by correlation.
(B) 1 & 3
(C) 2 & 3
(D) All of the above
Q109: A class of 60 pupils is randomly divided into three equal-sized classes. All partitions have an equal chance of occurring. Raj and Deep are two of the pupils in that group. What is the probability that Raj and Deep will be in the same class?
Q110: Ahmed is participating in a lottery game in which he must select two numbers ranging from 0 to 9, followed by an English alphabet (from 26-letters). He has the option of selecting the same number both times. If his ticket matches the two numbers and one letter chosen in the correct order, he wins the big prize of $10405. He gets $100 if only his letter matches but one or both of the digits do not match. In every other case, he loses everything. He has to pay $5 to play the game. Assume he’s selected 04R to play. What is the expected net profit from purchasing this ticket?