scoring-functions-nominal: Log score for categorical outcomes

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

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)

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.

Value

A numeric vector of size n with log scores

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)

epiforecasts/scoringutils documentation built on Dec. 11, 2024, 11:12 a.m.