Measure to compare true observed labels with predicted probabilities in multiclass classification tasks.

## Arguments

- truth
(

`factor()`

)

True (observed) labels. Must have the same levels and length as`response`

.- prob
(

`matrix()`

)

Matrix of predicted probabilities, each column is a vector of probabilities for a specific class label. Columns must be named with levels of`truth`

.- sample_weights
(

`numeric()`

)

Vector of non-negative and finite sample weights. Must have the same length as`truth`

. The vector gets automatically normalized to sum to one. Defaults to equal sample weights.- eps
(

`numeric(1)`

)

Probabilities are clipped to`max(eps, min(1 - eps, p))`

. Otherwise the measure would be undefined for probabilities`p = 0`

and`p = 1`

.- ...
(

`any`

)

Additional arguments. Currently ignored.