return (invisible(NULL))
}
V <- length(private$pmodels)
- oneLineX <- as.data.frame(t(as.matrix(X[1,])))
+ oneLineX <- t(as.matrix(X[1,]))
if (length(private$pmodels[[1]]$model(oneLineX)) >= 2)
# Soft classification:
return (Reduce("+", lapply(private$pmodels, function(m) m$model(X))) / V)