Question

Consider the following statements in the context of Artificial Intelligence. Which of the statement(s) given is/are correct ?

1. Perceptron specifies all actions that need to be undertaken and specifies the order only when required.
2. Inductive machine learning derives the conclusion and then improves it based on the previous decisions.
3. Training scenario and feedback does not affect the performance of learner system
4. Pattern matching allows computers to understand associations and relationships between objects and events.

• A. 4 only
• B. 1, 4
• C. None of these
• D. 1, 3

Answer 1

Answer:

A. 4 only

Perceptrons

• Perceptrons are a type of artificial neural network used for binary classification tasks.
• They do not specify actions or orders of actions; instead, they learn to make binary decisions based on input data and associated weights.
• So, statement (i) is incorrect.

Inductive machine learning

• Inductive machine learning is a type of machine learning in which the algorithm learns from data to make generalizations or predictions rather than deriving conclusions and then improving them based on previous decisions.
• Inductive learning involves generalizing from specific examples to make predictions about new, unseen data points.
• So, statement (ii) is incorrect

Training scenario and feedback

• Training scenarios and feedback are crucial in machine learning.
• The quality and quantity of training data, as well as the feedback provided to the learner system, have a significant impact on its performance and ability to generalize from the data.
• So, statement (iii) is incorrect.

Pattern matching

• Pattern matching is a fundamental concept in computer science and artificial intelligence (AI).
• It refers to the process of identifying and recognizing patterns or similarities between data points, objects, or events. 
• These patterns can be in the form of sequences of symbols, images, text, or any other type of data.
• So, statement (iv) is correct.