loglossBinary: Logarithmic Loss Function for Binary Models
In lares: Analytics & Machine Learning Sidekick
loglossBinary R Documentation
Logarithmic Loss Function for Binary Models
Description
This function calculates log loss/cross-entropy loss for binary
models. NOTE: when result is 0.69315, the classification is neutral;
it assigns equal probability to both classes.
Usage
loglossBinary(tag, score, eps = 0.001)
Arguments
tag
Vector. Real known label
score
Vector. Predicted value or model's result
eps
Numeric. Epsilon value
See Also
Other Model metrics:
ROC(),
conf_mat(),
errors(),
gain_lift(),
model_metrics()
lares documentation built on Sept. 13, 2024, 1:08 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.
| loglossBinary | R Documentation |
Logarithmic Loss Function for Binary Models
Description
This function calculates log loss/cross-entropy loss for binary models. NOTE: when result is 0.69315, the classification is neutral; it assigns equal probability to both classes.
Usage
loglossBinary(tag, score, eps = 0.001)
Arguments
tag |
Vector. Real known label |
score |
Vector. Predicted value or model's result |
eps |
Numeric. Epsilon value |
See Also
Other Model metrics:
ROC(),
conf_mat(),
errors(),
gain_lift(),
model_metrics()
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.