scoringutils (version 2.1.0)

logs_categorical: Log score for categorical outcomes

Description

Log score for categorical (nominal or ordinal) outcomes

The Log Score is the negative logarithm of the probability assigned to the observed value. It is a proper scoring rule. Small values are better (best is zero, worst is infinity).

Usage

logs_categorical(observed, predicted, predicted_label)

Value

A numeric vector of size n with log scores

Arguments

observed

Factor of length n with N levels holding the observed values.

predicted

nxN matrix of predictive probabilities, n (number of rows) being the number of observations and N (number of columns) the number of possible outcomes.

predicted_label

Factor of length N, denoting the outcome that the probabilities in predicted correspond to.

Input format

Overview of required input format for nominal forecasts

See Also

Other log score functions: logs_sample(), scoring-functions-binary

Examples

factor_levels <- c("one", "two", "three")
predicted_label <- factor(c("one", "two", "three"), levels = factor_levels)
observed <- factor(c("one", "three", "two"), levels = factor_levels)
predicted <- matrix(
  c(0.8, 0.1, 0.1,
    0.1, 0.2, 0.7,
    0.4, 0.4, 0.2),
  nrow = 3,
  byrow = TRUE
)
logs_categorical(observed, predicted, predicted_label)