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machine learning algorithm

What is the difference between induction learning algorithm and analogy learning algorithm?

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Difference between Induction Learning and Analogy Learning Algorithms

Learning by Analogy Algorithm Learning by Induction Algorithm
It is a process of learning a new concept or solution through the use of similar known concepts or solutions. Inductive learning is the system that tries to induce a general rule based on observed instances.
This system finds a common substructure between the problem domain and one of the analogous domains stored in the learner’s existing knowledge base. This system tries to infer an association between specific inputs and outputs.
This strategy requires more inferencing by the learning system. This strategy requires less inferencing by the learning system.
Analogy method involves learning by inductive inference, deductive inference, and systems existing knowledge. Induction method involves learning by examples, experimentation, observation, and discovery.
Learning by analogy is also used by humans more frequently. Generally inductive learning is frequently used by humans.
It is one of the types of single-agent learning. It is one of the types of single-agent learning.
This form of learning is less powerful. This form of learning is more powerful than the others.
Example, The driving technique of vehicles. If anyone knows the driving procedure of a bike, then that person will drive a car by using some sort of previous learning procedures. Example, humans can say the taste of sugar is sweet because they have the knowledge about sweetness.
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