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51.

How the decision tree reaches its decision?(a) Single test(b) Two test(c) Sequence of test(d) No testThis question was addressed to me in an internship interview.This interesting question is from Learning topic in portion Learning of Artificial Intelligence

Answer»

Correct answer is (C) SEQUENCE of test

Explanation: A decision tree REACHES its decision by performing a sequence of TESTS.

52.

What takes input as an object described by a set of attributes?(a) Tree(b) Graph(c) Decision graph(d) Decision treeI have been asked this question by my school teacher while I was bunking the class.This is a very interesting question from Learning topic in portion Learning of Artificial Intelligence

Answer» RIGHT answer is (d) Decision tree

The explanation is: Decision tree takes input as an object DESCRIBED by a SET of attributes and returns a decision.
53.

What will happen if the hypothesis space contains the true function?(a) Realizable(b) Unrealizable(c) Both Realizable & Unrealizable(d) None of the mentionedThis question was addressed to me in unit test.I want to ask this question from Learning topic in section Learning of Artificial Intelligence

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Correct answer is (b) Unrealizable

The EXPLANATION is: A learning problem is realizable if the hypothesis space CONTAINS the TRUE FUNCTION.

54.

Which is used to choose among multiple consistent hypotheses?(a) Razor(b) Ockham razor(c) Learning element(d) None of the mentionedI got this question by my school principal while I was bunking the class.This interesting question is from Learning topic in chapter Learning of Artificial Intelligence

Answer»

Correct choice is (b) Ockham razor

The best I can explain: Ockham razor PREFERS the SIMPLEST hypothesis CONSISTENT with the data intuitively.

55.

Which is used for utility functions in game playing algorithm?(a) Linear polynomial(b) Weighted polynomial(c) Polynomial(d) Linear weighted polynomialThis question was addressed to me in unit test.This interesting question is from Learning in chapter Learning of Artificial Intelligence

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The CORRECT ANSWER is (d) LINEAR weighted polynomial

Explanation: Linear weighted polynomial is used for LEARNING element in the game playing PROGRAMS.

56.

How many types are available in machine learning?(a) 1(b) 2(c) 3(d) 4The question was asked in unit test.This interesting question is from Learning in portion Learning of Artificial Intelligence

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Right OPTION is (C) 3

To EXPLAIN: The three types of machine LEARNING are supervised, unsupervised and REINFORCEMENT.

57.

What is used in determining the nature of the learning problem?(a) Environment(b) Feedback(c) Problem(d) All of the mentionedThe question was posed to me during an interview.Question is from Learning in portion Learning of Artificial Intelligence

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Correct choice is (b) FEEDBACK

The explanation is: The TYPE of feedback is used in DETERMINING the nature of the learning problem that the agent faces.

58.

Which modifies the performance element so that it makes better decision?(a) Performance element(b) Changing element(c) Learning element(d) None of the mentionedThis question was posed to me during an online interview.This interesting question is from Learning in section Learning of Artificial Intelligence

Answer»

The correct OPTION is (c) LEARNING element

Easiest EXPLANATION: A learning element MODIFIES the performance element so that it can make better DECISION.

59.

How many things are concerned in the design of a learning element?(a) 1(b) 2(c) 3(d) 4I got this question in exam.I want to ask this question from Learning in section Learning of Artificial Intelligence

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Correct ANSWER is (c) 3

The EXPLANATION is: The three main issues are affected in design of a learning element are components, FEEDBACK and REPRESENTATION.

60.

What will take place as the agent observes its interactions with the world?(a) Learning(b) Hearing(c) Perceiving(d) SpeechI have been asked this question in an interview.I need to ask this question from Learning topic in division Learning of Artificial Intelligence

Answer»

The correct answer is (a) LEARNING

Easiest explanation: Learning will TAKE place as the AGENT observes its interactions with the WORLD and its own decision making process.