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Tell us how do deductive and inductive machine learning differ?
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Answer / Amardeep Kumar
Deductive machine learning (also known as rule-based learning) applies a set of explicitly defined rules to make predictions or decisions. It is based on the principles of logic and reasoning, where conclusions are drawn from given premises through formal deduction. In contrast, inductive machine learning uses data and statistical methods to identify patterns and make generalizations about the underlying data distribution. Inductive learning algorithms (such as neural networks and support vector machines) learn from examples without being explicitly programmed with specific rules.
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