Description Usage Arguments Details Value Author(s) See Also Examples
Generate the control parameters for resampling or validation process.
1 |
sampling |
Sampling scheme. Valid options are:
|
niter |
Number of iteration or repeat for validation. |
nreps |
Number of replications in each iteration (number of folds for |
strat |
A logical value indicating if stratification is applied to
|
div |
Proportion of training data randomly selected for |
valipars
provides a list of control parameters for the resampling or validation
in the process of accuracy evaluation or feature selection process.
An object of class valipars
containing all the above
parameters (either the defaults or the user specified values).
Wanchang Lin wll@aber.ac.uk
1 2 3 4 5 6 7 8 9 10 11 | ## generate control parameters for the re-sampling scheme with 5-fold
## cross-validation and iteration of 10 times
valipars(sampling = "cv", niter = 10, nreps = 5)
## generate control parameters for the re-sampling scheme with
## 25-replication bootstrap and iteration of 100 times
valipars(sampling = "boot", niter = 100, nreps = 25,strat=TRUE)
## generate control parameters for the re-sampling scheme with
## leave-one-out cross-validation
valipars(sampling = "loocv")
|
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