Candidate Elimination Algorithm MCQ

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• It is possible that in the output, set S contains only phi.
  ক

  False

  খ

  True
• G = (<sunny, ?, ?, ?> ; <?, warm, ?, ?> ; <?, ?, high, ?>). Training data = <sunny, warm, normal, same> => Yes (positive example). How will G be represented after encountering this training data?
  ক

  <phi, phi, phi, phi>

  খ

  (<sunny, ?, ?, ?> ; <?, warm, ?, ?> ; <?, ?, high, ?>)

  গ

  (<sunny, ?, ?, ?> ; <?, warm, ?, ?>)

  ঘ

  <?, ?, ?, ?>
• G = <?, ?, ?, ?>. Training data = <sunny, warm, normal, same> => Yes (positive example). How will G be represented after encountering this training data?
  ক

  <sunny, warm, normal, same>

  খ

  <phi, phi, phi, phi>

  গ

  <rainy, cold, normal, change>

  ঘ

  <?, ?, ?, ?>
• S = <phi, phi, phi, phi>Training data = <rainy, cold, normal, change> => No (negative example). How will S be represented after encountering this training data?
  ক

  <phi, phi, phi, phi>

  খ

  <sunny, warm, high, same>

  গ

  <rainy, cold, normal, change>

  ঘ

  <?, ?, ?, ?>
• S = <sunny, warm, high, same>. Training data = <sunny, warm, normal, same> => Yes (positive example). How will S be represented after encountering this training data?
  ক

  <sunny, warm, high, same>

  খ

  <phi, phi, phi, phi>

  গ

  <sunny, warm, ?, same>

  ঘ

  <sunny, warm, normal, same>
• Let S be the set of maximally specific hypotheses. While iterating through the dataset, when is it changed for the first time?
  ক

  Negative example is encountered for the first time

  খ

  Positive example is encountered for the first time

  গ

  First example encountered, irrespective of whether it is positive or negative

  ঘ

  G, the set of maximally general hypotheses, is changed
• Let G be the set of maximally general hypotheses. While iterating through the dataset, when is it changed for the first time?
  ক

  Negative example is encountered for the first time

  খ

  Positive example is encountered for the first time

  গ

  First example encountered, irrespective of whether it is positive or negative

  ঘ

  S, the set of maximally specific hypotheses, is changed
• How is the version space represented?
  ক

  Least general members

  খ

  Most general members

  গ

  Most general and least general members

  ঘ

  Arbitrary members chosen form hypothesis space
• Candidate-Elimination algorithm can be described by ____________
  ক

  just a set of candidate hypotheses

  খ

  depends on the dataset

  গ

  set of instances, set of candidate hypotheses

  ঘ

  just a set of instances
• The algorithm is trying to find a suitable day for swimming. What is the most general hypothesis?
  ক

  A rainy day is a positive example

  খ

  A sunny day is a positive example

  গ

  No day is a positive example

  ঘ

  Every day is a positive example