= Rule-based machine learning
{wiki=Rule-based_machine_learning}
Rule-based machine learning refers to a class of algorithmic approaches that utilize rules to make decisions or predictions based on input data. These rules are usually derived from the data itself, expert knowledge, or a combination of both. Rule-based systems can be particularly useful in situations where interpretability and transparency are important, as the rules provide a clear, understandable way of representing the logic behind the decisions made by the system.
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