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Bias-Variance Tradeoff in Machine Learning
The bias-variance tradeoff is a fundamental concept in machine learning that helps explain why models may underperform on new, unseen data. This guide breaks down the nature of bias and variance, their impact on predictive errors, and strategies to manage them effectively for better model generalization.
The bias-variance tradeoff is a fundamental concept in machine learning that helps explain why models may underperform on new, unseen data. This guide breaks down the nature of bias and variance, their impact on predictive errors, and strategies to manage them effectively for better model generalization.
