Which of these approaches builds a predictive model by training it on input data?
Machine learning is the discipline focused on using algorithms that learn patterns from input (training) data to build predictive models capable of making forecasts or decisions on new, unseen data. This contrasts with expert systems, which rely on manually defined rules and a static knowledge base rather than learning from data, and with artificial intelligence, which is the overarching field encompassing many techniques (including machine learning, expert systems, and others) for simulating intelligent behavior but does not itself denote the specific data-driven training process.
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