#!/usr/bin/Rscript library(e1071) data <- as.matrix(read.table("08_twofeature_forR.txt", header=T)) # standardize data[,2] <- (data[,2]-mean(data[,2]))/sd(data[,2]) data[,3] <- (data[,3]-mean(data[,3]))/sd(data[,3]) plot(data[,2], data[,3], col=data[,1]+2) model <- svm(data[,2:3], data[,1], method="linear", cost=1) beta <- t(model$SV) %*% model$coefs beta0 <- model$rho abline(beta[1]/beta[2], beta0) model2 <- svm(data[,2:3], data[,1], method="linear", cost=100) beta <- t(model2$SV) %*% model2$coefs beta0 <- model2$rho abline(beta[1]/beta[2],beta0, col=2) p <- predict(model, data[,2:3]) p2 <- predict(model2, data[,2:3]) print(table(p>0, data[,1]>0)) print(table(p2>0, data[,1]>0))