Make a loess curve with loess() to predict the test error for different values of C by interpolating the passed evaluated
points on the tbl dataframe.
Usage
make.CV.chart(tbl, plot = TRUE, ...)
Arguments
tbl
Table from find.CV.C
plot
TRUE means plot the chart. False means do not, but return the optimal C
...
Parameters to the plot function
Value
invisible list of the minimum C value and the estimated test error for both the minimum
and the predicted C corresponding to 1 SE above the minimum estimate.
Details
Then plot the test error with SE bars for the cross validation. Also calculate the spot that is 1 SE above the minimum.
Fits the points with loess lines so, in principle, few actually evaluated points are needed in evaluating the function.
All a bit ad hoc and worthy of improvement.