Dear respected colleagues, kindly let me know your opinion on specific differences and similarities between a inductive and deductive learning in machine learning. Or is there any difference in definition for inductive and deductive in your field? Thanks.
In the most basic sense, most of statistical or machine learning is based on inductive reasoning, where we we can suggest statements, not state facts. Whereas, Expert Systems are based on deductive reasoning, and aims to generate facts.
The difference between inductive and deductive learning and how they relate to machine learning is beautifully explained in the following post
https://www.quora.com/What-is-inductive-learning-and-what-is-deductive-learning-in-artificial-intelligence-To-which-type-of-learning-do-the-following-algorithms-belong-kNN-Neural-Networks-SVM
◆Inductive AI (Statistical AI) coming from machine learning tends to embark on the path of "inductive" cogitation: Given a set of patterns, induces the trends. (e.g. Neural Networks)
◆Deductive AI (Classic AI) focuses on the "deductive" thought: Given a set of
constraints, the conclusion is derived. (e.g. Fuzzy Logic、Expert Systems、Control Technologies、Evolutionary Algorithms、. . .)
Dear Dr.Jyh-Horng Chou and all
Thank you so much for your explanation
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