summary.mclustDAtrain {mclust} | R Documentation |
The models selected in mclustDAtrain
and the corresponding classfications.
summary.mclustDAtrain(object, ...)
object |
The output of mclustDAtrain .
|
... |
Not used. For generic/method consistency. |
A list identifying the model selected by
mclustDAtrain
for each
class of training data and the corresponding classification.
C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631. See http://www.stat.washington.edu/mclust.
C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.
set.seed(0) n <- 100 ## create artificial data x <- rbind(matrix(rnorm(n*2), n, 2) %*% diag(c(1,9)), matrix(rnorm(n*2), n, 2) %*% diag(c(1,9))[,2:1]) xclass <- c(rep(1,n),rep(2,n)) ## Not run: par(pty = "s") mclust2Dplot(x, classification = xclass, type="classification", ask=FALSE) ## End(Not run) odd <- seq(1, 2*n, 2) train <- mclustDAtrain(x[odd, ], labels = xclass[odd]) ## training step summary(train)