Lecture

Model Selection and Evaluation: Bias-Variance Dilemma, Ridge Estimation

In course

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Description

This lecture covers the concepts of over-learning, generalization, and under-learning in machine learning models. It explains the bias-variance tradeoff, approximation errors, and the ridge regression technique. The instructor illustrates how to select the optimal model and discusses the impact of bias and variance on model performance.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_03zh3m3s

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Ontological neighbourhood

Statistics

Data analysis: Cross-validation, Regression analysis

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