# R/print.cca.R In ConsRankClass: Classification and Clustering of Preference Rankings

#### Documented in print.cca

```#'S3 methods for cca
#'
#'Print methods for objects of class \code{cca}
#'
#'@param x An object of the class "cca"
#'@param \dots not used
#'
#'@return print a brief summary of the CCA
#'
#'
#'@export

print.cca <- function(x,...){

rescca<-x

obj <- "\nK-Median Cluster Component Analysis: \n"
cat(obj)
cat("Components extracted: ",ncol(rescca\$pk), ".\n\n", sep='')
cat("Cluster centers: ", "\n")
cat(rescca\$oclc[1,], "\n")
for (j in 2:nrow(rescca\$clc)){
cat(rescca\$oclc[j,], "\n")
}
cat("\n")
cat("Global homogeneity: ", format(rescca\$Hcca,digits=3), ".\n", sep='')
cat("Estimated proportions: ", paste(format(c(rescca\$props), digits=3), collapse=';'), ".\n", sep='')
cat("Internal homogeneity: ", paste(format(c(rescca\$hk), digits=3), collapse=';'), ".\n\n", sep='')
cat("Overall classifiability (normalized geometric mean): ", format(rescca\$Ucca, digits=3), ".\n", sep='')
cat("Overall classifiability (normalized probabilities prod): ", format(rescca\$Uprodscca, digits=3), ".\n\n", sep='')
cat("Algorithm used to compute median rankings: ", rescca\$settings\$algorithm, ".\n")
cat("\n")

}
```

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ConsRankClass documentation built on Sept. 28, 2021, 5:10 p.m.