evolutionary algorithm: A class of optimization algorithms encouraged by the process of natural range. These algorithms iteratively increase methods to complicated complications by way of mechanisms like mutation, crossover, and selection.
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regularization: Methods utilized all through model instruction to avoid overfitting by including constraints or penalties on the product's complexity. Frequent techniques contain L1 and L2 regularization.
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classification: The job of predicting a discrete label or class for any provided input dependant on figured out styles from instruction facts. Popular applications contain spam detection and image recognition.
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