S5E09 Regularized Variable Selection Methods
Quantitude
Regularized Variable Selection Methods in Regression Analysis
The chapter explores the concept of regularization and its applications in statistics, focusing on variable selection methods in regression analysis. It discusses the goal of selecting a smaller set of variables for prediction and the potential issues with variable selection. The speakers also touch on the trade-off between unbiasedness and replicability, as well as the bias-variance trade-off and the concept of root mean square error.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
