Machine Learning MCQs with answers Page - 1

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Q. Support vectors are the data points that lie closest to the decision

  • (A) TRUE
  • (B) 1 and 3
  • (C) ---
  • (D) ---

A

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Q. How can we assign the weights to output of different models in an ensemble?
1. Use an algorithm to return the optimal weights
2. Choose the weights using cross validation
3. Give high weights to more accurate models

  • (A) 1 and 2
  • (B) o(tkn)
  • (C) 2 and 3
  • (D) all of above

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Q. The main disadvantage of maximum likelihood methods is that they are . . . . . . . .

  • (A) mathematically less folded
  • (B) mathematically less complex
  • (C) mathematically less complex
  • (D) computationally intense

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Q. Frequent item sets is

  • (A) superset of only closed frequent item sets
  • (B) superset of only maximal frequent item sets
  • (C) subset of maximal frequent item sets
  • (D) superset of both closed frequent item sets and maximal frequent item sets

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Q. If there is only a discrete number of possible outcomes called . . . . . . . .

  • (A) Modelfree
  • (B) Categories
  • (C) Prediction
  • (D) None of above

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Q. Which of the following algorithm comes under the classification

  • (A) apriori
  • (B) brute force
  • (C) dbscan
  • (D) k-nearest neighbor

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Q. Which of the following are real world applications of the SVM?

  • (A) Text and Hypertext Categorization
  • (B) Image Classification
  • (C) Clustering of News Articles
  • (D) All of the above

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Q. . . . . . . . . dataset with many features contains information proportional to the independence of all features and their variance.

  • (A) normalized
  • (B) unnormalized
  • (C) Both A and B
  • (D) None of the Mentioned

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Q. Which of the following sentences are true?

  • (A) in pre-pruning a tree is pruned by halting its construction early
  • (B) a pruning set of class labelled tuples is used to estimate cost complexity
  • (C) the best pruned tree is the one that minimizes the number of encoding bits
  • (D) all of the above

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Q. Which of the following are advantages of stacking?
1. More robust model
2. better prediction
3. Lower time of execution

  • (A) 1 and 2
  • (B) 2 and 3
  • (C) 1 and 3
  • (D) all of the above

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