Description Usage Arguments Details Value References See Also Examples
TODO Split a data set into testing and training samples by leaving selectors out. If more than one response (i.e. dependent) variable is supplied, a different set of testing/training pairs is created for each of them. The training/testing samples leave one or more selectors completely out. Selectors can be something like individual locations, a certain time step or a combination of both. Basically, it can be anything since the selector variable is defined by the user and hence it can be compiled in such a way that it leaves out whatever the user wants.
1 2 3 4 5 6 | ## S4 method for signature 'GPM'
createIndexFolds(x, nested_cv = FALSE, nbr = 1)
## S4 method for signature 'data.frame'
createIndexFolds(x, response, resamples, selector,
nested_cv = FALSE, nbr = 1)
|
x |
An object of class gpm or data.frame |
response |
The column name(s) of the response variable(s) |
resamples |
The list of the resamples containing the individual row
numbers (resulting from function |
selector |
The column name of the selector variable. Only relevant if use_selector is TRUE. |
p |
The fraction of each sample to be used for model training (default 0.75) |
use_selector |
Use the selector variable for splitting the samples into training or testing (default FALSE). |
The split into training and testing samples is realized by using the caret::createDataPartition function which preserves the frequency distribution of the individual response variable(s).
A layer within the gpm object with the information on the n individual resamplings.
A nested list with training and testing samples for each of the n resamplings.
The function uses functions from: Max Kuhn. Contributions from Jed Wing, Steve Weston, Andre Williams, Chris Keefer, Allan Engelhardt, Tony Cooper, Zachary Mayer, Brenton Kenkel, the R Core Team, Michael Benesty, Reynald Lescarbeau, Andrew Ziem, Luca Scrucca, Yuan Tang and Can Candan. (2016). caret: Classification and Regression Training. https://CRAN.R-project.org/package=caret
resamplingsByVariable
for creating n resamplings from
the original dataset.
1 2 3 4 | ## Not run:
#Not run
## End(Not run)
|
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