```
X <- iris[,1:4]
class <- iris$Species
# randomly remove class labels
set.seed(123)
class[sample(1:length(class), size = 120)] <- NA
table(class, useNA = "ifany")
clPairs(X, ifelse(is.na(class), 0, class),
symbols = c(0, 16, 17, 18), colors = c("grey", 4, 2, 3),
main = "Partially classified data")
# Fit semi-supervised classification model
mod_SSC <- MclustSSC(X, class)
summary(mod_SSC, parameters = TRUE)
pred_SSC <- predict(mod_SSC)
table(Predicted = pred_SSC$classification, Actual = class, useNA = "ifany")
plot(mod_SSC, what = "BIC")
plot(mod_SSC, what = "classification")
plot(mod_SSC, what = "uncertainty")
```

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