Thursday, 13 August 2020

CS607-Artificial Intelligence Quiz MCQs Lecture 23-45 Finalterm Objective Questions | SUPERSTARWEBTECH



CS607-Artificial Intelligence Quiz MCQS #Objective #Questions #FinalTerm

1. Inductive Learning is based on the knowledge that if something happens a lot it is likely to be generally ___
  • True ✔
  • False
  • Ambiguous
  • None
2. If the antecedent is only partially true, then the output fuzzy set is truncated according to the ___ method.
  • Intrinsic
  • Implication ✔
  • Boolean
  • None
3. The input of aggregation process is the list of truncated output functions returned by the ___ process for each rule.
  • Truncation
  • Implication ✔
  • Aggregation
  • None
4. ___ learning works on existing facts and knowledge and deduces new knowledge from the old.
  • Deductive ✔
  • Inductive
  • Application
  • None
5. Machine learning typically follows ___ phases according to Finlay.
  • Two
  • Three ✔
  • Four
  • Five
6. Which one is NOT the phase of machine learning:
  • Training
  • Application
  • Validation
  • None ✔
7. In theoretical computer science there are two main branches of problems.
  • Tractable and Intractable ✔
  • Intractable and Induction
  • Tractable and Induction
  • None
8. ___ is the process by which the fuzzy sets that represent the outputs of each rule are combined into a single fuzzy set.
  • Aggregation ✔
  • Fuzzification
  • Implication
  • None
9. Outputs of learning are determined by the ___
  • Application ✔
  • Validation
  • Training
  • None
10. ___ is the process of formulating the mapping from a given input to an output using Fuzzy logic.
  • FIZ
  • FIS ✔
  • FOS
  • None
11. The brain is a collection of about 100 ___ interconnected neurons.
  • Million
  • Billion ✔
  • Trillion
  • None
12. A single Perceptron simply draws a line, which is a hyper plane when the data is ___ than/to two (2) dimensional.
  • More ✔
  • Less
  • Equal
  • None
13. In Candidate-Elimination algorithm version space is represented by two sets named:
  • G and S ✔
  • G and F
  • S and F
  • H and S
14. The first step of FIND-S is to initialize h to the most specific hypothesis in ___ : h<>
  • H ✔
  • I
  • J
  • K
15. Decision trees give us disjunctions of conjunctions, that is, they have the form: (A AND B) ___ (C AND D)
  • OR ✔
  • AND
  • XOR
  • None
16. Interactive Dichotomizer uses a special function ___, to evaluate the gain information of each attribute.
  • GAIN ✔
  • GET
  • FIND
  • EVAL
17. Measure of the effectiveness of an attribute in classifying the training data is called
  • Information Gain ✔
  • Measure Gain
  • Information Goal
  • None
18. Artificial Neural Networks is a new learning paradigm which takes its roots from ___ inspired approach to learning.
  • Chemistry
  • Physics
  • Biology ✔
  • Mathematics
19. Which one is NOT the advantage of Neural Network
  • Excellent for pattern recognition
  • Excellent classifiers
  • Handles noisy data well
  • None ✔
20. In all calculations involving Entropy we define ___ to be ___
  • 0 log 0, 0 ✔
  • 0 log 10, 1
  • 0 log 0, 1
  • 1 log 1, 1