evaluate_model: Compute and print metrics for classification model evaluation
In dfsp-spirit/brainnet: Machine learning on structural neuroimaging data for R
evaluate_model R Documentation
Compute and print metrics for classification model evaluation
Description
Compute and print metrics for classification model evaluation
Usage
evaluate_model(actual, predicted)
Arguments
actual
vector of actual labels
predicted
vector of predicted labels
Value
Nothing, called for printing side effect.
Author(s)
T Schaefer
dfsp-spirit/brainnet documentation built on July 11, 2022, 5:54 a.m.
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.
| evaluate_model | R Documentation |
Compute and print metrics for classification model evaluation
Description
Compute and print metrics for classification model evaluation
Usage
evaluate_model(actual, predicted)
Arguments
actual |
vector of actual labels |
predicted |
vector of predicted labels |
Value
Nothing, called for printing side effect.
Author(s)
T Schaefer
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.