MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Explanation: Inductive learning involves finding a consistent hypothesis that agrees with examples. The difficulty of the task depends on the chosen representation. Explanation: Computational learning theory analyzes the sample complexity and computational complexity of inductive learning.

Detailed explanation-2: -The inductive learning hypothesis states that any hypothesis found to approximate the target function well over a sufficiently large set of training examples will also approximate the target function well over other unobserved examples.

Detailed explanation-3: -1 Answer. For explanation: Inductive learning involves finding a consistent hypothesis that agrees with examples.

Detailed explanation-4: -Inductive training information is obtained through observation, and analytical training information is obtained by explaining and analyzing these observations in terms of the learner’s prior knowledge.

Detailed explanation-5: -Inductive Learning is where we are given examples of a function in the form of data (x) and the output of the function (f(x)). The goal of inductive learning is to learn the function for new data (x). Classification: when the function being learned is discrete. Regression: when the function being learned is continuous.