modPermute: Permute Features in Data
In tpq/exprso: Rapid Deployment of Machine Learning Algorithms
Description
Usage
Arguments
Value
Description
modPermute randomly shuffles each feature across
all samples in the data. Using permuted data can establish
a null model for testing the significance of prediction
error estimates. This approach preserves the univariate
distributions, but will change the multivariate
distribution.
Usage
1
modPermute(object)
Arguments
object
An ExprsArray object to undergo pre-processing.
Value
An ExprsArray object.
tpq/exprso documentation built on July 27, 2019, 8:44 a.m.
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Description Usage Arguments Value
Description
modPermute randomly shuffles each feature across
all samples in the data. Using permuted data can establish
a null model for testing the significance of prediction
error estimates. This approach preserves the univariate
distributions, but will change the multivariate
distribution.
Usage
1 | modPermute(object)
|
Arguments
object |
An |
Value
An ExprsArray object.
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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