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logloss

Log Loss

Description

Classification measure defined as

-mean(log(p))

where p is the probability for the true class of observation i.

Usage

logloss(truth, prob, eps = 1e-15, ...)

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.
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.

Value

Performance value as numeric(1).

Meta Information

  • Type: "classif"

  • Range: [0, Inf)

  • Minimize: TRUE

  • Required prediction: prob

See Also

Other Classification Measures: acc(), bacc(), ce(), mauc_aunu(), mbrier()

Examples

set.seed(1)
lvls = c("a", "b", "c")
truth = factor(sample(lvls, 10, replace = TRUE), levels = lvls)
prob = matrix(runif(3 * 10), ncol = 3, dimnames = list(NULL, lvls))
prob = t(apply(prob, 1, function(x) x / sum(x)))
logloss(truth, prob)
mlr3measures

Performance Measures for 'mlr3'

v0.3.1
LGPL-3
Authors
Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Martin Binder [ctb]
Initial release

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