accuracy.MC: Estimate assignment accuracies of Monte-Carlo...
In assignPOP: Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine Learning Framework
Description
Usage
Arguments
Value
Description
This function allows you to estimate assignment accuracies of Monte-Carlo cross-validation results. The output results can be used to make assignment accuracy plots (use function accuracy.plot).
Usage
1
accuracy.MC(dir = NULL)
Arguments
dir
A character string to specify the folder that has your Monte-Carlo cross-validation results. A slash should be included at the end (e.g., dir="YourFolderName/").
Value
This function outputs the results in a text file (a table). It can return a data frame when a returning object is specified.
assignPOP documentation built on Oct. 28, 2021, 1:06 a.m.
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Description Usage Arguments Value
Description
This function allows you to estimate assignment accuracies of Monte-Carlo cross-validation results. The output results can be used to make assignment accuracy plots (use function accuracy.plot).
Usage
1 | accuracy.MC(dir = NULL)
|
Arguments
dir |
A character string to specify the folder that has your Monte-Carlo cross-validation results. A slash should be included at the end (e.g., dir="YourFolderName/"). |
Value
This function outputs the results in a text file (a table). It can return a data frame when a returning object is specified.
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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