--- title: "Overfitting with linear regression" output: html_document: default pdf_document: default --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` We'll reproduce the example given on page 11 of _Statistical Learning with Sparsity: the Lasso and Generalizations_ by Hastie, Tibshirani, and Wainwright. (Code by Seth Flaxman). ```{r, fig.width=10 } data = read.csv("crime.txt",sep="\t") names(data) = c("overall","violent","funding","hs","not-hs","college","college4") library(glmnet) library(plotmo) data$overall = log10(data$overall) par(mfrow=c(1,2)) fit.lasso = glmnet(data.matrix(data[,3:7]),data$overall) plot.glmnet(fit.lasso,xvar="lambda") fit.l2 = glmnet(data.matrix(data[,3:7]),data$overall,alpha=0) plot.glmnet(fit.l2,xvar="lambda") fit.lasso = cv.glmnet(data.matrix(data[,3:7]),data$overall) plot(fit.lasso) fit.l2 = cv.glmnet(data.matrix(data[,3:7]),data$overall,alpha=0) plot(fit.l2) ```