loglossBinary: Logarithmic Loss Function for Binary Models
In laresbernardo/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()
laresbernardo/lares documentation built on Oct. 23, 2024, 12:05 p.m.
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| 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.
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