Match List I with List II List–I (Term) List–II (Definition) (A) Natural…
2024
Match List I with List II
List–I (Term) | List–II (Definition) |
|---|---|
(A) Natural language processing | (I) A method of training an algorithm by rewarding desired behaviour and punishing undesired behaviour. |
(B) Reinforcement learning | (II) System designed to emulate the decision-making abilities of a human expert. |
(C) Support vector machine | (III) A branch of AI focused on understanding and generating human language. |
(D) Expert system | (IV) A machine-learning technique that finds the hyperplane that best separates different classes in a feature space. |
Choose the correct answer from the options given below:
- A.
(A)-(I), (B)-(II), (C)-(IV), (D)-(III)
- B.
(A)-(III), (B)-(II), (C)-(I), (D)-(IV)
- C.
(A)-(III), (B)-(I), (C)-(IV), (D)-(II)
- D.
(A)-(II), (B)-(IV), (C)-(III), (D)-(I)
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Correct answer: C
Correct matching:
Natural language processing — a branch of AI focused on understanding and generating human language.
Reinforcement learning — a method of training algorithms by rewarding desired behaviour and/or punishing undesired behaviour.
Support vector machine — a machine learning technique that finds the hyperplane that best separates different classes in a feature space.
Expert system — a system designed to emulate the decision-making abilities of a human expert.
Brief reasoning:
Natural language processing is explicitly about human language tasks (understanding/generation), so it matches that definition.
Reinforcement learning is defined by learning through rewards and punishments, which distinguishes it from supervised or unsupervised methods.
Support vector machines are geometric classifiers that choose a hyperplane to separate classes, matching the hyperplane description.
Expert systems encapsulate domain knowledge and decision rules to emulate human expert decision-making.
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