Bias-Variance Trade-Off: Revision history

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    5 November 2024

    • curprev 07:4907:49, 5 November 2024핵톤 talk contribs 6,277 bytes +6,277 Created page with "The Bias-Variance Trade-Off is a fundamental concept in machine learning that describes the balance between two sources of error that affect model performance: bias and variance. The goal is to achieve a balance between bias and variance that minimizes the model’s total error, enabling it to generalize well to new, unseen data. ==Understanding Bias and Variance== *'''Bias''': Refers to the error introduced by approximating a complex real-world problem with a simplified..." Tag: Visual edit