kfold: Determine k-fold partitions for a given number of samples
In marchtaylor/sinkr: Collection of functions with emphasis in multivariate data analysis
kfold R Documentation
Determine k-fold partitions for a given number of samples
Description
Determine k-fold partitions for a given number of samples
Usage
kfold(n, k = NULL)
Arguments
n
number of samples
k
number of partitions (Defaults to n; i.e. "leave-one-out")
Details
For specific use in cross validation (see cv.nperm)
Value
a list containing sample numbers in each partition
Examples
res <- kfold(100,6)
res
length(res) # partition indices
unlist(lapply(res, length)) # number of samples in each partition
marchtaylor/sinkr documentation built on July 4, 2022, 5:48 p.m.
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| kfold | R Documentation |
Determine k-fold partitions for a given number of samples
Description
Determine k-fold partitions for a given number of samples
Usage
kfold(n, k = NULL)
Arguments
n |
number of samples |
k |
number of partitions (Defaults to n; i.e. "leave-one-out") |
Details
For specific use in cross validation (see cv.nperm)
Value
a list containing sample numbers in each partition
Examples
res <- kfold(100,6) res length(res) # partition indices unlist(lapply(res, length)) # number of samples in each partition
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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