balanced.cv.fold: Split a dataset for Cross Validation taking into account...
In bmrm: Bundle Methods for Regularized Risk Minimization Package
Description
Usage
Arguments
Value
Description
Split a dataset for Cross Validation taking into account class balance
Usage
1
balanced.cv.fold(y, num.cv = 10)
Arguments
y
the class labels of each sample of the dataset
num.cv
number of cross validation required
Value
a factor of num.cv levels that assign to each sample a test fold
bmrm documentation built on May 2, 2019, 2:49 p.m.
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Description Usage Arguments Value
Description
Split a dataset for Cross Validation taking into account class balance
Usage
1 | balanced.cv.fold(y, num.cv = 10)
|
Arguments
y |
the class labels of each sample of the dataset |
num.cv |
number of cross validation required |
Value
a factor of num.cv levels that assign to each sample a test fold
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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