Q. PCA is

  • (A) forward feature selection
  • (B) backword feature selection
  • (C) feature extraction
  • (D) all of the above
πŸ’¬ Discuss
βœ… Correct Answer: (C) feature extraction

Q. Dimensionality reduction algorithms are one of the possible ways to reduce the computation time required to build a model.

  • (A) true
  • (B) false
  • (C) ---
  • (D) ---
πŸ’¬ Discuss
βœ… Correct Answer: (A) true

Q. Which of the following techniques would perform better for reducing dimensions of a data set?

  • (A) removing columns which have too many missing values
  • (B) removing columns which have high variance in data
  • (C) removing columns with dissimilar data trends
  • (D) none of these
πŸ’¬ Discuss
βœ… Correct Answer: (A) removing columns which have too many missing values

Q. Supervised learning and unsupervised clustering both require which is correct according to the statement.

  • (A) output attribute.
  • (B) hidden attribute.
  • (C) input attribute.
  • (D) categorical attribute
πŸ’¬ Discuss
βœ… Correct Answer: (C) input attribute.

Q. What characterize is hyperplance in geometrical model of machine learning?

  • (A) a plane with 1 dimensional fewer than number of input attributes
  • (B) a plane with 2 dimensional fewer than number of input attributes
  • (C) a plane with 1 dimensional more than number of input attributes
  • (D) a plane with 2 dimensional more than number of input attributes
πŸ’¬ Discuss
βœ… Correct Answer: (B) a plane with 2 dimensional fewer than number of input attributes

Q. In multiclass classification number of classes must be

  • (A) less than two
  • (B) equals to two
  • (C) greater than two
  • (D) option 1 and option 2
πŸ’¬ Discuss
βœ… Correct Answer: (C) greater than two

Q. Which of the following can only be used when training data are linearlyseparable?

  • (A) linear hard-margin svm
  • (B) linear logistic regression
  • (C) linear soft margin svm
  • (D) the centroid method
πŸ’¬ Discuss
βœ… Correct Answer: (A) linear hard-margin svm

Q. Impact of high variance on the training set ?

  • (A) overfitting
  • (B) underfitting
  • (C) both underfitting & overfitting
  • (D) depents upon the dataset
πŸ’¬ Discuss
βœ… Correct Answer: (A) overfitting

Q. What do you mean by a hard margin?

  • (A) the svm allows very low error in classification
  • (B) the svm allows high amount of error in classification
  • (C) both 1 & 2
  • (D) none of the above
πŸ’¬ Discuss
βœ… Correct Answer: (A) the svm allows very low error in classification

Q. The effectiveness of an SVM depends upon:

  • (A) selection of kernel
  • (B) kernel parameters
  • (C) soft margin parameter c
  • (D) all of the above
πŸ’¬ Discuss
βœ… Correct Answer: (A) selection of kernel

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