In our data-science class, after discussing limitations of the logistic regression, e.g. the fact that the decision boundary line was a straight line, we’ve mentioned possible natural extensions. Let us consider our (now) standard dataset clr1 <- c(rgb(1,0,0,1),rgb(0,0,1,1)) clr2 <- c(rgb(1,0,0,.2),rgb(0,0,1,.2)) x <- c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) y <- c(.85,.95,.8,.87,.5,.55,.5,.2,.1,.3) z <- c(1,1,1,1,1,0,0,1,0,0) df <- data.frame(x,y,z) plot(x,y,pch=19,cex=2,col=clr1) One can consider a quadratic...