Plot function summarizing some results from double-crossvalidation of lpls-regression/classification.
# S3 method for lplsReg.dcv plot(object, identifyVariable = FALSE)
| object | A double-Cv object as returned from |
|---|---|
| identifyVariable | Logical. Should interactive variable identification be activated? |
The first plot is a plot of posterior probability of class membership for each sample plotted versus sample number. For g-group classification, there will be g dots per sample, and the largest dot indicates the predicted class/group. The second plot is a plot of the frequency of each variable being selected by jack-knifing in each of the cross-validation segments. High selection frequency may be considered as a measure of variable importance and stability.