I've been working with an 'evolutionary tree' package known as 'evtree,' but unfortunately I've ran into some obstacles in terms of accuracy-type measures for the package.
I wondered if anyone would be able to help provide some code in terms of obtaining an AUC for classification-type data, and MSE for regression-type analysis.
The authors have provided some example code:
X1 <- rep(seq(0.25, 1.75, 0.5), each = 4) X2 <- rep(seq(0.25, 1.75, 0.5), 4) Y <- rep(1, 16) Y[(X1 < 1 & X2 < 1) | (X1 > 1 & X2 > 1)] <- 2 Y <- factor(Y, labels = c("O", "X")) chess22 <- data.frame(Y, X1, X2) ## trees library("evtree") set.seed(1090) evtree(Y ~ ., data = chess22, minbucket = 1, minsplit = 2)
Would be appreciated if someone could help with some code in terms of generating accuracy-type measures like AUC/MSE following the evtree function.