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Objective Function in Machine Learning

In machine learning, an objective function quantifies the goal of an algorithm, which is typically to minimize an error measure (a cost function) or maximize a probability function. For supervised learning problems like classification and prediction, an error function is defined to capture the discrepancy between the known correct outputs and the model's predicted outputs. The learning process then aims to find model parameters that minimize this function.

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Updated 2026-05-02

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