Summarizing discriminant analysis based on Gaussian finite mixture modeling
Summary method for class "MclustDA"
.
## S3 method for class 'MclustDA' summary(object, parameters = FALSE, newdata, newclass, ...) ## S3 method for class 'summary.MclustDA' print(x, digits = getOption("digits"), ...)
object |
An object of class |
x |
An object of class |
parameters |
Logical; if |
newdata |
A data frame or matrix giving the test data. |
newclass |
A vector giving the class labels for the observations in the test data. |
digits |
The number of significant digits to use when printing. |
... |
Further arguments passed to or from other methods. |
The function summary.MclustDA
computes and returns a list of summary statistics of the estimated MclustDA or EDDA model for classification.
Luca Scrucca
mod = MclustDA(data = iris[,1:4], class = iris$Species) summary(mod) summary(mod, parameters = TRUE)
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