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Restrict generation of confusion matrix for resamples when number of classes is large #356

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merged 1 commit into from Mar 17, 2016
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4 pkg/caret/R/workflows.R
@@ -274,7 +274,7 @@ nominalTrainWorkflow <- function(x, y, wts, info, method, ppOpts, ctrl, lev, tes
model = method)
if(testing) print(head(thisResample))
## for classification, add the cell counts
- if(length(lev) > 1)
+ if(length(lev) > 1 && length(lev) <= 50)
{
cells <- lapply(predicted,
function(x) flatTable(x$pred, x$obs))
@@ -311,7 +311,7 @@ nominalTrainWorkflow <- function(x, y, wts, info, method, ppOpts, ctrl, lev, tes
model = method)
## if classification, get the confusion matrix
- if(length(lev) > 1) thisResample <- c(thisResample, flatTable(tmp$pred, tmp$obs))
+ if(length(lev) > 1 && length(lev) <= 50) thisResample <- c(thisResample, flatTable(tmp$pred, tmp$obs))
thisResample <- as.data.frame(t(thisResample))
thisResample <- cbind(thisResample, info$loop[parm,,drop = FALSE])