Machine Learning: MCQs Set – 14

Q131: Classification problems are distinguished from estimation problems in that

  • (A) classification problems require the output attribute to be numeric
  • (B) classification problems require the output attribute to be categorical
  • (C) classification problems do not allow an output attribute
  • (D) classification problems are designed to predict future outcome

Q132: Let’s say your model is overfitting. Which of the following is NOT a suitable method for attempting to decrease overfitting?

  • (A) Increase the amount of training data
  • (B) Improve the optimization algorithm being used for error minimization.
  • (C) Decrease the model complexity.
  • (D) Reduce the noise in the training data.

Q133: When doing least-squares regression with regularization (assuming that the optimization can be done exactly), increasing the value of the regularization parameter(Lambda)?

  • (A) will never decrease the training error
  • (B) will never increase the training error
  • (C) will never decrease the testing error
  • (D) will never increase the testing error.

Q134: Which of the following is a common use of unsupervised clustering?

  • (A) detect outliers
  • (B) determine a best set of input attributes for supervised learning
  • (C) evaluate the likely performance of a supervised learner model
  • (D) determine if meaningful relationships can be found in a dataset

Q135: In which neural net architecture, does weight sharing occur?

  • (A) Convolutional neural Network
  • (B) Recurrent Neural Network
  • (C) Fully Connected Neural Network
  • (D) Both A and B

Q136: Neural networks

  • (A) optimize a convex cost function
  • (B) always output values between 0 and 1
  • (C) can be used for regression as well as classification 
  • (D) can be used in an ensemble

Q137: For feature selection, both PCA and Lasso can be utilized. Which of the following assertions is NOT correct?

  • (A) Lasso selects a subset (not necessarily a strict subset) of the original features
  • (B) PCA and Lasso both allow you to specify how many features are chosen
  • (C) PCA produces features that are linear combinations of the original features
  • (D) PCA and Lasso are the same if you use the kernel trick

Q138: A researcher concludes from his analysis that a placebo cures AIDS. What type of error is he making?

  • (A) Type 1 error
  • (B) Type 2 error
  • (C) No error
  • (D) Cannot be determined

Q139: When an event A independent of itself?

  • (A) Always
  • (B) If and only if P(A)=0
  • (C) If and only if P(A)=1
  • (D) If and only if P(A)=0 or 1

Q140: HIV is still a very scary disease to even get tested for. The US military tests its recruits for HIV when they are recruited. They are tested on three rounds of Elisa( an HIV test) before they are termed to be positive. The prior probability of anyone having HIV is 0.00148. The true positive rate for Elisa is 93% and the true negative rate is 99%. What is the probability of having HIV, given he tested positive on Elisa the second time as well. The prior probability of anyone having HIV is 0.00148. The true positive rate for Elisa is 93% and the true negative rate is 99%.

  • (A) 20%
  • (B) 42%
  • (C) 93%
  • (D) 88%

Answers:

QuestionQ131Q132Q133Q134Q135Q136Q137Q138Q139Q140
AnswerCBAADC, DA, CDDC

≪ Previous | Next ≫