| predict.MclustDA {mclust} | R Documentation |
Classify multivariate observations based on Gaussian finite mixture models estimated by MclustDA.
## S3 method for class 'MclustDA' predict(object, newdata, prior, ...)
object |
an object of class |
newdata |
a data frame or matrix giving the data. If missing the train data obtained from the call to |
prior |
the prior probabilities of the classes; by default, this is set at the proportions in the training data. |
... |
further arguments passed to or from other methods. |
Returns a list of with the following components:
classification |
a factor of predicted class labels for |
z |
a matrix whose [i,k]th entry is the probability that
observation i in |
Luca Scrucca
C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611:631.
C. Fraley, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.
## Not run: odd <- seq(from = 1, to = nrow(iris), by = 2) even <- odd + 1 X.train <- iris[odd,-5] Class.train <- iris[odd,5] X.test <- iris[even,-5] Class.test <- iris[even,5] irisMclustDA <- MclustDA(X.train, Class.train) predTrain <- predict(irisMclustDA) predTrain predTest <- predict(irisMclustDA, X.test) predTest ## End(Not run)