balanced_accuracy: Balanced Accuracy
In computational-metabolomics/structtoolbox: Data processing & analysis tools for Metabolomics and other omics
View source: R/balanced_accuracy_class.R
balanced_accuracy R Documentation
Balanced Accuracy
Description
Balanced Accuracy is the average proportion of correctly classified samples across all groups.
Usage
balanced_accuracy(...)
Arguments
...
Additional slots and values passed to struct_class.
Value
A
balanced_accuracy
object. This object has no output slots.
Inheritance
A balanced_accuracy object inherits the following struct classes:
[balanced_accuracy] >> [metric] >> [struct_class]
Examples
M = balanced_accuracy()
D = iris_DatasetExperiment()
XCV = kfold_xval(folds=5,factor_name='Species') *
(mean_centre() + PLSDA(number_components=2,factor_name='Species'))
MET = balanced_accuracy()
XCV = run(XCV,D,MET)
computational-metabolomics/structtoolbox documentation built on Feb. 9, 2024, 8:19 a.m.
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View source: R/balanced_accuracy_class.R
| balanced_accuracy | R Documentation |
Balanced Accuracy
Description
Balanced Accuracy is the average proportion of correctly classified samples across all groups.
Usage
balanced_accuracy(...)
Arguments
... |
Additional slots and values passed to |
Value
A
balanced_accuracy
object. This object has no output slots.
Inheritance
A balanced_accuracy object inherits the following struct classes:
[balanced_accuracy] >> [metric] >> [struct_class]
Examples
M = balanced_accuracy()
D = iris_DatasetExperiment()
XCV = kfold_xval(folds=5,factor_name='Species') *
(mean_centre() + PLSDA(number_components=2,factor_name='Species'))
MET = balanced_accuracy()
XCV = run(XCV,D,MET)
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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