Nothing
what.else <- function(nn) {
if(is.pnn.trained && !is.pnn.smoothed) {
message(paste(
"PNN trained with", nn$n, "observations describing",
length(nn$categories), "categories with", nn$k, "variables."
), sep=" ")
message("Ready to be smoothed with function 'smooth'")
return(TRUE)
} else {
message(
"This object is not a Probabilist neural network from the package PNN."
)
message("Please, use another appropriate function.")
return(FALSE)
}
}
is.data.frame.with.real.variables <- function(df) {
for( i in 1:length(df[1,]) ) { if( !is.numeric(df[,i]) ) return(FALSE) }
return(TRUE)
}
is.trainingset.correct <- function(nn) {
if(
is.data.frame(nn)
&& is.factor(nn$set[,nn$category_column])
&& is.data.frame.with.real.variables(nn$set[,-nn$category_column])
) return(TRUE) else return(FALSE)
}
is.pnn.trained <- function(nn) {
if(
is.data.frame(nn)
&& !is.null(nn$model)
&& !is.null(nn$set)
&& !is.null(nn$category.column)
&& !is.null(nn$categories)
&& !is.null(nn$k)
&& !is.null(nn$n)
) return(TRUE) else return(FALSE)
}
is.pnn.smoothed <- function(nn) {
if(
is.pnn.trained(nn)
&& !is.null(nn$sigma)
) return(TRUE) else return(FALSE)
}
is.pnn.performed <- function(nn) {
if(
is.pnn.smoothed(nn)
&& !is.null(nn$observed)
&& !is.null(nn$guessed)
&& !is.null(nn$success)
&& !is.null(nn$fails)
&& !is.null(nn$success_rate)
&& !is.null(nn$bic)
) return(TRUE) else return(FALSE)
}
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