Machine Learning & Training

What Is the Bias-Variance Tradeoff?

The bias-variance tradeoff describes the tension between two sources of error in machine learning models. High bias leads to underfitting, where the model is too simple, while high variance leads to overfitting, where the model is too sensitive to training data. Good models balance these to achieve strong generalization.