Machine Learning MCQ Multiple Choice Questions - Page 2 for Practice
Machine Learning MCQ Questions for Practice
31. You observe the following while fitting a linear regression to the data: As you increase the amount of training data, the test error decreases and the training error increases. The train error is quite low (almost what you expect it to), while the test error is much higher than the train error. What do you think is the main reason behind this behavior. Choose the most probable option.
Correct Answer is: None of the above
32. A measure of goodness of fit for the estimated regression equation is the
Correct Answer is: none of the above
33. A nearest neighbor approach is best used
Correct Answer is: when an explanation of what has been found is of primary importance.
34. A regression model in which more than one independent variable is used to predict the dependent variable is called
Correct Answer is: none of the above
35. A term used to describe the case when the independent variables in a multiple regression model are correlated is
Correct Answer is: none of the above
36. Adding more basis functions in a linear model... (pick the most probably option)
Correct Answer is: Doesnt affect bias and variance
37. Another name for an output attribute.
Correct Answer is: dependent variable
38. Bootstrapping allows us to
Correct Answer is: test a model with alternative subsets of the test data several times.
39. Choose the options that are correct regarding machine learning (ML) and artificial intelligence (AI),(A) ML is an alternate way of programming intelligent machines.(B) ML and AI have very different goals.(C) ML is a set of techniques that turns a dataset into a software.(D) AI is a software that can emulate the human mind.
Correct Answer is: All are correct
40. Classification problems are distinguished from estimation problems in that
Correct Answer is: classification problems are designed to predict future outcome.
41. Computational complexity of Gradient descent is
Correct Answer is: dependent on the number of iterations
42. Computers are best at learning
Correct Answer is: principles.
43. Consider a binary classification problem. Suppose I have trained a model on a linearly separable training set, and now I get a new labeled data point which is correctly classified by the model, and far away from the decision boundary. If I now add this new point to my earlier training set and re-train, in which cases is the learnt decision boundary likely to change?
Correct Answer is: When my model is a perceptron
44. Data used to build a data mining model.
Correct Answer is: hidden data
45. Data used to optimize the parameter settings of a supervised learner model.
Correct Answer is: verification
46. Generalization error measures how well an algorithm perform on unseen data. The test error obtained using cross-validation is an estimate of the generalization error. Is this estimate unbiased?
Correct Answer is: Yes
47. Grid search is
Correct Answer is: Polynomial in D and Linear in N
48. K-fold cross-validation is
Correct Answer is: exponential in K
49. Let us say that we have computed the gradient of our cost function and stored it in a vector g. What is the cost of one gradient descent update given the gradient?
Correct Answer is: O(ND2)
50. Logistic regression is a ........... regression technique that is used to model data having a ........... outcome.
Correct Answer is: nonlinear, numeric
51. Machine learning techniques differ from statistical techniques in that machine learning methods
Correct Answer is: have trouble with large-sized datasets
52. Regarding bias and variance, which of the follwing statements are true? (Here high and low are relative to the ideal model)
Correct Answer is: Models which overfit have a low bias and underfit have a high variance.
