RECITATION 4 MAY 23 DPMM Splines with multiple predictors Classification and regression trees.

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RECITATION 4 MAY 23 DPMM Splines with multiple predictors Classification and regression trees

Dirichlet Process Mixture Model Library “DPpackage” R Demo 1

Spline method with multiple predictors Generalized Additive Model Natural Thin Plate Splines The minimizer of (RSS+“bending energy”) among all interpolators with knots at the observations. Form:

Spline method with multiple predictors Thin Plate Regression Splines Optimal approximation of thin plate splines using low rank basis No need to choose knots Tensor Product Splines Basis: product of basis (truncated spline) of each dimension R Demo 2

Classification and regression trees Classification tree The response is binary or categorical outcome. Regression tree The response is a continuous variable. The predicted value will be the same for all data points in a leaf node. “Grow” the tree and then “prune” it by minimizing cross validation error R Demo 3

Course Evaluation Thanks!