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Lecture
Error Decomposition and Regression Methods
Description
This lecture covers error decomposition in regression, including reducible and irreducible errors, polynomial regression for flexible modeling, and K Nearest-Neighbors for non-linear predictions. It also discusses underfitting, overfitting, and the bias-variance trade-off.
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