Explain the concepts of bias, variance, model complexity, and the bias-variance trade-off.

Free SOA Exam PA (Predictive Analytics) lesson in Predictive Analytics Problem Definition. 8 min read, ~1,185 words.

Bias is error from oversimplifying; a too rigid model underfits and misses the true signal. Variance is how much the fitted model swings when the training sample changes; flexible models overfit. Model complexity (flexibility) lowers bias but raises variance. Expected test MSE equals variance plus bias squared plus irreducible error...

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