loglossBinary: Logarithmic Loss Function for Binary Models

Description Usage Arguments See Also

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

1
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 June 9, 2021, 9:06 a.m.