search for: ct_cv

...], unsound[even_u == 1,]) p <- rbind(sound[even_s != 1,], unsound[even_u != 1,]) fit <- lda(samples ~., data = t) ct <- table(p[, 1], predict(fit, p[,-1])$class) errors <- 1-diag(prop.table(ct, 1)) min.err <- 1-sum(diag(prop.table(ct))) fit_cv <- lda(samples ~., data = r, CV =T) ct_cv <- table(r[,1], fit_cv$class) errors_cv <- 1-diag(prop.table(ct_cv, 1)) min.err_cv <- 1-sum(diag(prop.table(ct_cv))) thank you for your help! Best regards, Roberto -- View this message in context: http://r.789695.n4.nabble.com/Different-results-between-lda-mass-and-spss-discriminant-a...