Q81: A term used to describe the case when the independent variables in a multiple regression model are correlated is
(D) none of the above
Q82: Machine learning techniques differ from statistical techniques in that machine learning methods
(A) typically assume an underlying distribution for the data
(B) are better able to deal with missing and noisy data
(C) are not able to explain their behavior.
(D) have trouble with large-sized datasets
Q83: This clustering algorithm initially assumes that each data instance represents a single cluster
(A) agglomerative clustering
(B) conceptual clustering
(C) K-Means clustering
(D) expectation maximization
Q84: Which of the following elements has no effect on the performance of the learner system?
(A) Representation scheme used
(B) Training scenario
(C) Type of feedback
(D) Good data structures
Q85: Assume we have a dataset that can be trained with 100 percent accuracy using a decision tree of depth 6. Consider the following points and select an option based on them. Note : All other hyperparameters are the same, and no other factors are impacted. (1). Depth 4 has a strong bias and a low variance. (2). Depth 4 will be low in bias and variance.
(A) Only 1
(B) Only 2
(C) Only 1 and 2
(D) None of the above
Q86: Which of the following assertions about bias and variance is true?
(A) Models which overfit have a high bias.
(B) Models which overfit have a low bias
(C) Models which underfit have a high variance
(D) Models which underfit have a low variance.
Q87: Consider one layer of weights (edges) in a grayscale convolutional neural network (CNN), which connects one layer of units to the next layer of units. Which layer contains the fewest parameters that must be learnt during training? (Choose one.)
(A) A convolutional layer with 10 3 × 3 filters
(B) A convolutional layer with 8 5 × 5 filters
(C) A max-pooling layer that reduces a 10 × 10 image to 5 × 5
(D) A fully-connected layer from 20 hidden units to 4 output units
Q88: Consider the regression line y = ax + b, where a represents the slope and b represents the intercept. If we know the value of the slope, how can we always get the value of the intercept?
(A) Put the value (0,0) in the regression line True
(B) Put any value from the points used to fit the regression line and compute the value of b False
(C) Put the mean values of x & y in the equation along with the value a to get b False
(D) None of the above can be used False
Q89: Six times a fair six-sided die is rolled. What is the probability of all outcomes being unique?
Q90: There are eight marbles in all, two each of green, yellow, orange, and red. How many different ways can you choose one marbel?