COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
Question
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Consistent Hypothesis


Inconsistent Hypothesis


Regular Hypothesis


Irregular Hypothesis

Detailed explanation1: 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 explanation2: 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 explanation3: 1 Answer. For explanation: Inductive learning involves finding a consistent hypothesis that agrees with examples.
Detailed explanation4: Inductive training information is obtained through observation, and analytical training information is obtained by explaining and analyzing these observations in terms of the learnerâ€™s prior knowledge.
Detailed explanation5: 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.