February 04, 2011

Using Nonparametric Smoothing in Regression (Advanced Data Analysis from an Elementary Point of View, Lecture 4)

The bias-variance trade-off tells us how much we should smooth; introduction to the Oracle. Our ignorance of both bias and variance, now that the Oracles have fallen silent. Estimating the sum of bias and variance with cross-validation. Adaptation as a substitute for knowledge. Adapting to unknown roughness with cross-validation; detailed examples. Using kernel regression with multiple inputs: multivariate kernels, product kernels. Using smoothing to automatically discover interactions. Plots to help interpret multivariate smoothing results. Appendix: the multivariate Gaussian distribution.



Advanced Data Analysis from an Elementary Point of View

Posted at February 04, 2011 01:33 | permanent link

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