print.upclassfit: Printing Classification Method
In upclass: Updated Classification Methods using Unlabeled Data

Description Usage Arguments Details Value Author(s) References See Also Examples

print method for class "upclassfit".

1 2	## S3 method for class 'upclassfit' print(x, ...)

`x`	an object of class `"upclassfit"`, the result of a call to `upclassify` or `noupclassify`.
`...`	further arguments passed to or from other methods.

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.

`modelName`	A character string identifying the model (same as the input argument).
`misclass`	The number of misclassified observations
`rate`	The percentage of misclassified observations

Niamh Russell

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.

summary.upclassfit, upclassify, noupclassify

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)