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What is the Bias Variance Dilemma in Machine Learning?
The Bias Variance Dilemma in Machine Learning refers to the trade-off between the bias of a model and its variance. Understanding this concept is crucial for building effective models. At Berkeley, researchers emphasize how overcoming this dilemma can improve the performance of machine learning systems.
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