@@ -381,6 +381,7 @@ setMethod("crossValidate", "matrix", # Matrix of numeric measurements.

 # This expects that each table is about the same set of samples and thus

 # has the same number of rows as every other table.

 #' @rdname crossValidate

+#' @importFrom S4Vectors combineRows                                                             

 #' @export

 setMethod("crossValidate", "list",

           function(measurements,

@@ -425,7 +426,13 @@ setMethod("crossValidate", "list",

               }, df_list, names(df_list))

-              combined_df <- do.call(cbind, df_list)

+              # combined_df <- do.call("cbind", df_list) was adding the list names to the colnames

+

+                combined_df <- df_list[[1]]

+                for(i in names(df_list)[-1]){

+                    combined_df <- S4Vectors::combineRows(combined_df, df_list[[i]], use.names=FALSE)

+                }

+

               crossValidate(measurements = combined_df,

                             outcome = outcome, 

@@ -1069,4 +1076,4 @@ predict.trainedByClassifyR <- function(object, newData, ...)

   } else if (is(object, "listOfModels")) { # Object is itself a trained model and it is assumed that a predict method is defined for it.

     mapply(function(model, assay) predict(model, assay), object, newData, SIMPLIFY = FALSE)

   } else predict(object, newData)

-}

\ No newline at end of file

+}