Discussion
Consider the following statements in the context of Artificial Intelligence.
(i) Perceptron specifies all actions that need to be undertaken and specifies the order only when required.
(ii) Inductive machine learning derives the conclusion and then improves it based on the previous decisions.
(iii) Training scenario and feedback does not affect the performance of learner system.
(iv) Pattern matching allows computers to understand associations and relationships between objects and events.
Which of the statement(s) given above is/are correct ?
Answer: D
Only statement (iv) is correct, so the answer is Only (iv).
Pattern matching is indeed how a computer recognises associations and relationships between objects and events, by comparing inputs with stored patterns (iv). It is the only option that includes (iv).
Statement (iii) is plainly wrong: the training scenarios and the feedback a learning system receives are what determine how well it performs, so option C fails. Statement (i) does not describe a perceptron, which is the simplest artificial neuron, a linear classifier that weighs inputs and fires above a threshold; specifying actions and their order is the job of a planner. Statement (ii) does not describe inductive learning, which generalises a rule from specific examples rather than starting from a conclusion. So options A and B are wrong as well.
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