upclass (version 2.0)

print.upclassfit: Printing Classification Method

Description

print method for class "upclassfit".

Usage

"print"(x, ...)

Arguments

x

an object of class "upclassfit", the result of a call to upclassify or noupclassify.

...

further arguments passed to or from other methods.

Value

modelName

A character string identifying the model (same as the input argument).

misclass

The number of misclassified observations

rate

The percentage of misclassified observations

Details

print.upclassfit gives a more concise output than summary.upclassfit. Any of the members of the list can be called using the names listed in the helptext for upclassify or noupclassify.

References

C. Fraley and A.E. Raftery (2002). Model based clusetering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

Fraley, C. and Raftery, A.E. (2006). MCLUST Version for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.

Dean, N., Murphy, T.B. and Downey, G (2006). Using unlabelled data to update classification rules with applications in food authenticity studies. Journal of the royal Statistical Society: Series C 55 (1), 1-14.

See Also

summary.upclassfit, upclassify, noupclassify

Examples

data(wine, package = "gclus")
X <- as.matrix(wine[, -1])
cl <- as.matrix(wine[, 1])
indtrain <- sort(sample(1:178, 120))
indtest <- setdiff(1:178, indtrain)

fitup <- upclassify(X[indtrain,], cl[indtrain], X[indtest,], cl[indtest])
print(fitup)