R/confusion.matrix.R

In profpetrie/regclass: Tools for an Introductory Class in Regression and Modeling

confusion.matrix <-
function(M,DATA=NA) {
    if(missing(DATA)) { DATA <- M$model }
    D <- names(DATA)
    y.label <- as.character(M$terms[[2]])
    y.pos <- which(D==y.label)
    y.levels <- names(table(DATA[,y.pos]))
    y.pred <- ifelse( predict(M,newdata=DATA,type="response") >= 0.5, y.levels[2],y.levels[1])
    T<-table(DATA[,y.pos],y.pred,dnn=c())
    if(  dim(T)[2]==1  )  {
        colnames(T) <- paste("Predicted",names(which.max(table(DATA[,y.pos]))))
        rownames(T) <- c(paste("Actual",y.levels))
        cat("Predicted levels same as naive model (majority level)\n");
        return(T) }
    T<-rbind(T,apply(T,2,sum))
    T<-cbind(T,apply(T,1,sum))
    colnames(T) <- c(paste("Predicted",y.levels),"Total")
    rownames(T) <- c(paste("Actual",y.levels),"Total")
    T }