Bias Variance

+**Bias Variance**

+Bias-variance is a fundamental dilemma in [Machine Learning](/wiki/Machine_Learning), revealing how a model's predictions vary from the true function. High bias means a model is too simple (underfitting), missing patterns, while high variance means it's too complex (overfitting), sensitive to noise and struggling with [Generalization](/wiki/Generalization) on unseen data.

+## See also

+- [Overfitting](/wiki/Overfitting)

+- [Underfitting](/wiki/Underfitting)