Quiz 100% Result
  • Cyberian's Gold

    1. If the true output of a concept [c(xi)] is 1 or 0 for an instance, then the output by our hypothesis [h(xi)] is 1 or 0 as well, respectively.
      A. True
      B. False

    2. Decision trees give us dis-junctions of conjunctions, that is, they have the form: (A AND B) _______ (C AND D).
      A. OR
      B. AND
      C. XOR
      D. None of the given

    3. Hypothesis space uses the ________________ of the attributes.
      A. Conjunctions (AND)
      B. Disjunctions (OR)
      C. Negation (NOR)
      D. None of the given

    4. Measure of the effectiveness of an attribute in classifying the training data is called.
      A. Information Gain
      B. Measure Gain
      C. Information Goal
      D. None of the given

    5. Which one is NOT the advantage of Neural Network
      A. Excellent for pattern recognition
      B. Excellent classifiers
      C. Handles noisy data well
      D. None of the given

    6. The first step of FIND-S is to initialize h to the most specific hypothesis in __________: h = < Ø , Ø >
      A. H
      B. I
      C. J
      D. K

    7. A drawback of FIND-S is that, it assumes the consistency within the training set.
      A. True
      B. False

    8. In all calculations involving Entropy we define _________ to be ______
      A. 0 log 0, 0
      B. 0 log 10, 1
      C. 0 log 0, 1
      D. 1 log 1, 1

    9. The soma and the enclosed nucleus in neuron play a significant role in the processing of incoming and outgoing data.
      A. True
      B. False

    10. A concept is the representation of the __________ with respect to the given attributes.
      A. Solution
      B. Problem
      C. Knowledge
      D. None of the given

  • Cyberian's Gold

    Inductive learning takes examples and generalizes rather than starting with __________ knowledge.

    Existing
    Inductive
    Deductive
    None of the given

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  • Cyberian's Gold

    In theoretical computer science there are two main branches of problems:

    Select correct option:
    Tractable and Intractable
    Intractable and Induction
    Tractable and Induction
    None of the given

    9a41b8cd-c0a4-4fc0-9f7d-5cb8d92ef956-image.png

  • Cyberian's Gold

    Which one is NOT the phase of machine learning:

    Select correct option:

    a. Validation
    b. Training
    c. Application
    d. none of given

    0f2572e8-d665-4070-9d51-789d83dd1ae0-image.png

  • Cyberian's Gold

    Decision trees give us disjunctions of conjunctions, that is, they have the form:
    (A AND B) _______ (C AND D).
    Ans: OR
    b51a0616-9d3f-417a-919c-22a312d7a75a-image.png

  • Cyberian's Gold

    The tractable problems are further divided into structured and ________ problems
    Ans: Complex

    a05c205f-fd04-4996-aff4-e4925704727f-image.png

  • Cyberian's Gold

    _____________ learning works on existing facts and knowledge and deduces new knowledge from the old.

    Ans: deductive

    e9e1068a-bf5b-423b-a5e8-ea34431e82d8-image.png

  • Cyberian's Gold

    A concept is the representation of the __________ with respect to the given attributes.

    Select correct option:

    Solution

    Problem

    Knowledge

    None of the given
    097fdddc-5a4e-4211-8c42-27e9d83ee31c-image.png

  • Cyberian's Gold

    Interactive Dichotomizer uses a special function ________, to evaluate the gain information of each attribute.

    GAIN
    002113c9-25ee-4af4-bc00-a6f5c1fefee1-image.png

  • Cyberian's Gold

    The Entropy is 1 when the collection contains number of positive examples _______ to/than negative examples.

    Select correct option:

    Equal

    Greater

    Less

    None of the given

    177c45f0-3211-4767-bf84-cf9597fa277a-image.png

  • Cyberian's Gold

    The Candidate-Elimination algorithm represents the ____________
    Version Space

    da4c630d-304c-4f53-ac8f-46238d1ea64a-image.png

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