Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/summary.upclassfit.R
summary
method for class "upclassfit"
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object |
an object of class |
... |
further arguments passed to or from other methods. |
summary.upclassfit
gives a fuller output than print.upclassfit
. Any of the members of the list can be called using the names listed in the helptext for upclassify
or noupclassify
.
Model Name |
A character string identifying the model (same as the input argument). |
Log Likelihood |
The log-likelihood for the data in the mixture model. |
Dimension |
The dimension of the data. |
Ntrain |
The number of observations in the training data. |
Ntest |
The number of observations in the test data. |
bic |
The Bayesian Information Criterion for the best model. |
misclass |
The number of misclassified observations (displayed only if labels are provided for the test data). |
rate |
The percentage of misclassified observations(displayed only if labels are provided for the test data). |
Niamh Russell
C. Fraley and A.E. Raftery (2002). Model based clustering, 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.
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