January 16, 2013

Lecture: Regression: Predicting and Relating Quantitative Features (Advanced Data Analysis from an Elementary Point of View)

Statistics is the branch of mathematical engineering which designs and analyzes methods for learning from imperfect data. Regression is a statistical model of functional relationships between variables. Getting relationships right means being able to predict well. The least-squares optimal prediction is the expectation value; the conditional expectation function is the regression function. The regression function must be estimated from data; the bias-variance trade-off controls this estimation. Ordinary least squares revisited as a smoothing method. Other linear smoothers: nearest-neighbor averaging, kernel-weighted averaging.

Reading: Notes, chapter 1 (examples.dat for running example; ckm.csv data set for optional exercises)

Advanced Data Analysis from an Elementary Point of View

Posted at January 16, 2013 23:15 | permanent link

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