Find-S Algorithm MCQ

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• The algorithm accommodates all the maximally specific hypotheses.
  ক

  True

  খ

  False
• S = <phi, phi, phi> Training data = <square, pointy, white> => Yes (positive example). How will S be represented after encountering this training data?
  ক

  <phi, phi, phi>

  খ

  <square, pointy, white >

  গ

  <circular, blunt, black>

  ঘ

  <?, ?, ? >
• Noise or errors in the dataset can severely affect the performance of the Find-S algorithm.
  ক

  True

  খ

  False
• What is one of the drawbacks of the Find-S algorithm?
  ক

  Computation cost is high

  খ

  Time-ineffective

  গ

  All correct hypotheses are not output

  ঘ

  Most specific accurate hypothesis is not output
• S = <phi, phi, phi>Training data = <rainy, cold, white> => No (negative example). How will S be represented after encountering this training data?
  ক

  <phi, phi, phi>

  খ

  <sunny, warm, white>

  গ

  <rainy, cold, black>

  ঘ

  <?, ?, ?>
• How does the hypothesis change gradually?
  ক

  Specific to Specific

  খ

  Specific to General

  গ

  General to Specific

  ঘ

  General to General
• What is one of the advantages of the Find-S algorithm?
  ক

  Computation is faster than other concept learning algorithms

  খ

  All correct hypotheses are output

  গ

  Most generalized hypothesis is output

  ঘ

  Overfitting does not occur
• What is one of the assumptions of the Find-S algorithm?
  ক

  No assumptions are made

  খ

  The most specific hypothesis is also the most general hypothesis

  গ

  All training data are correct (there is no noise)

  ঘ

  Overfitting does not occur
• When does the hypothesis change in the Find-S algorithm, while iteration?
  ক

  Any example (positive or negative) is encountered

  খ

  Amy negative example is encountered

  গ

  Positive Example inconsistent with the hypothesis is encountered

  ঘ

  Any positive example is encountered
• What is present in the version space of the Find-S algorithm in the beginning?
  ক

  Set of all hypotheses H

  খ

  Both maximally general and maximally specific hypotheses

  গ

  Maximally general hypothesis

  ঘ

  Maximally specific hypothesis