Machine Learning (ML) MCQs | Page - 42

Dear candidates you will find MCQ questions of Machine Learning (ML) here. Learn these questions and prepare yourself for coming examinations and interviews. You can check the right answer of any question by clicking on any option or by clicking view answer button.

M

Mr. Dubey • 97.30K Points
Coach

Q. The cost parameter in the SVM means:

  • (A) the number of cross- validations to be made
  • (B) the kernel to be used
  • (C) the tradeoff between misclassification and simplicity of the model
  • (D) none of the above
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M

Mr. Dubey • 97.30K Points
Coach

Q. If you remove the non-red circled points from the data, the decision boundary will

  • (A) true
  • (B) false
  • (C) ---
  • (D) ---
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M

Mr. Dubey • 97.30K Points
Coach

Q. How do you handle missing or corrupted data in a dataset?

  • (A) drop missing rows or columns
  • (B) replace missing values with mean/median/mode
  • (C) assign a unique category to missing values
  • (D) all of the above
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M

Mr. Dubey • 97.30K Points
Coach

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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M

Mr. Dubey • 97.30K Points
Coach

Q. Some people are using the term instead of prediction only to avoid the weird idea that machine learning is a sort of modern magic.

  • (A) inference
  • (B) interference
  • (C) accuracy
  • (D) none of above
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M

Mr. Dubey • 97.30K Points
Coach

Q. The term can be freely used, but with the same meaning adopted in physics or system theory.

  • (A) accuracy
  • (B) cluster
  • (C) regression
  • (D) prediction
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M

Mr. Dubey • 97.30K Points
Coach

Q. Common deep learning applications / problems can also be solved using

  • (A) real-time visual object identification
  • (B) classic approaches
  • (C) automatic labeling
  • (D) bio-inspired adaptive systems
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M

Mr. Dubey • 97.30K Points
Coach

Q. Identify the various approaches for machine learning.

  • (A) concept vs classification learning
  • (B) symbolic vs statistical learning
  • (C) inductive vs analytical learning
  • (D) all above
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M

Mr. Dubey • 97.30K Points
Coach

Q. what is the function of Unsupervised Learning?

  • (A) find clusters of the data and find low-dimensional representations of the data
  • (B) find interesting directions in data and find novel observations/ database cleaning
  • (C) interesting coordinates and correlations
  • (D) all
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M

Mr. Dubey • 97.30K Points
Coach

Q. What are the two methods used for the calibration in Supervised Learning?

  • (A) platt calibration and isotonic regression
  • (B) statistics and informal retrieval
  • (C) ---
  • (D) ---
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