@@ -300,7 +300,7 @@

     modellingParams@trainParams@otherParams <- tuneChosen

   }

-  if(attr(modellingParams@trainParams@classifier, "name") != "previousTrained")

+    if (!"previousTrained" %in% attr(modellingParams@trainParams@classifier, "name")) 

     # Don't name these first two variables. Some classifier functions might use classesTrain and others use outcomeTrain.

     paramList <- list(measurementsTrain, outcomeTrain)

   else # Don't pass the measurements and classes, because a pre-existing classifier is used.

@@ -641,4 +641,4 @@

 .dmvnorm_diag <- function(x, mean, sigma) { # Remove once sparsediscrim is reinstated to CRAN.

   exp(sum(dnorm(x, mean=mean, sd=sqrt(sigma), log=TRUE)))

-}

\ No newline at end of file

+}