aggregateCVSingle: Aggregate and Save Cross-validation Result for Single-omics...
In SmCCNet: Sparse Multiple Canonical Correlation Network Analysis Tool
aggregateCVSingle R Documentation
Aggregate and Save Cross-validation Result for Single-omics Analysis
Description
Saves cross-validation results in a table with the
user-defined directory and outputs penalty term with the highest testing canonical correlation,
lowest prediction error, and lowest scaled prediction error.
Usage
aggregateCVSingle(CVDir, SCCAmethod = "SmCCA", K = 5, NumSubsamp = 500)
Arguments
CVDir
A directory where the result is stored.
SCCAmethod
The canonical correlation analysis method that is used in
the model, used to name cross-validation table file, default is set to 'SmCCA'.
K
number of folds for cross-validation.
NumSubsamp
Number of subsampling used.
Value
A vector of length 3 with indices of the penalty term that (1) maximize the testing canonical correlation,
(2) minimize the prediction error and (3) minimize the scaled prediction error.
SmCCNet documentation built on May 29, 2024, 10:49 a.m.
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| aggregateCVSingle | R Documentation |
Aggregate and Save Cross-validation Result for Single-omics Analysis
Description
Saves cross-validation results in a table with the user-defined directory and outputs penalty term with the highest testing canonical correlation, lowest prediction error, and lowest scaled prediction error.
Usage
aggregateCVSingle(CVDir, SCCAmethod = "SmCCA", K = 5, NumSubsamp = 500)
Arguments
CVDir |
A directory where the result is stored. |
SCCAmethod |
The canonical correlation analysis method that is used in the model, used to name cross-validation table file, default is set to 'SmCCA'. |
K |
number of folds for cross-validation. |
NumSubsamp |
Number of subsampling used. |
Value
A vector of length 3 with indices of the penalty term that (1) maximize the testing canonical correlation, (2) minimize the prediction error and (3) minimize the scaled prediction error.
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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