Bias-Variance and Generalization

Model Robustness

Bias-Variance and Generalization

Model complexity, noise, and the gap between fitting and learning.

What This Shows

Change model complexity and data conditions to see how training fit can diverge from generalization. The applet turns overfitting into an observable behavior rather than an abstract warning, making it useful for model selection and risk-aware validation.

Generalization Bias-variance Validation Model selection Regularization

Technical Challenge

Distinguishing useful flexibility from unstable fitting under noisy data.

My Contribution

Created an interactive simulator for comparing training behavior with out-of-sample performance.

Industry Transfer

Experiment design, forecasting, predictive maintenance, risk models, applied ML validation.

Connected Work

Mercado Libre experimentation and robust scientific inference.