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.
loglossBinary(tag, score, eps = 0.000000000000001)
Vector. Real known label
Vector. Predicted value or model's result
Numeric. Epsilon value
Other Calculus: ROC
, conf_mat
,
corr
, deg2num
,
dist2d
, errors
,
mae
, mape
,
model_metrics
, mse
,
quants
, rmse
,
rsqa
, rsq