DATABASE FUNDAMENTALS
DATA WAREHOUSING AND DATA MINING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Machine-learning involving different techniques
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The learning algorithmic analyzes the examples on a systematic basis and makes incremental adjustments to the theory that is learned
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Learning by generalizing from examples
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None of the above
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Detailed explanation-1: -Inductive learning is a type of machine learning that uses data to make predictions or generalizations about a given problem. It is based on the idea that if a set of data points have certain characteristics, then future data points will also have those characteristics.
Detailed explanation-2: -Inductive learning, also known as discovery learning, is a process where the learner discovers rules by observing examples. This is different from deductive learning, where students are given rules that they then need to apply.
Detailed explanation-3: -Inductive teaching and learning is an umbrella term that encompasses a range of instructional methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching.
Detailed explanation-4: -Explanation: Inductive learning is used to find a consistent hypothesis, which agrees with the examples. The difficulty of the task relies on the chosen representation.
Detailed explanation-5: -A classical example of an inductive bias is Occam’s Razor, which expresses a preference for simplicity: Given two models that both explain the training data equally well, the simpler one should be preferred as a generalization.