Machine Learning MCQ Questions and Answers Quiz

51. Which statement about outliers is true?

  1. Outliers should be identified and removed from a dataset.
  2. Outliers should be part of the training dataset but should not be present in the test data.
  3. Outliers should be part of the test dataset but should not be present in the training data.
  4. The nature of the problem determines how outliers are used.

52. Which statement is true about neural network and linear regression models?

  1. Both models require input attributes to be numeric.
  2. Both models require numeric attributes to range between 0 and 1.
  3. The output of both models is a categorical attribute value.
  4. Both techniques build models whose output is determined by a linear sum of weighted input attribute values.

53. With Bayes classifier, missing data items are

  1. treated as equal compares.
  2. treated as unequal compares.
  3. replaced with a default value.
  4. ignored.

54. 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.

  1. High variance
  2. High model bias
  3. High estimation bias
  4. None of the above
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