multiClassSummary: Multi-class summary metrics

In specmine: Metabolomics and Spectral Data Analysis and Mining

Multi-class summary metrics

Description

Compute overall and class-averaged performance metrics for multiclass classification models, including ROC AUC and log-loss when class probabilities are available.

Usage

multiClassSummary(data, lev = NULL, model = NULL)

Arguments

data	A data frame containing at least the columns 'pred' and 'obs', plus one probability column per class when ROC or log-loss are needed.
lev	An optional character vector with the class levels.
model	An optional fitted model object passed by 'caret'.

Value

A named numeric vector with overall and class-averaged classification statistics.

Examples

data <- data.frame(
  pred = factor(c("A", "B", "A", "B"), levels = c("A", "B")),
  obs = factor(c("A", "B", "B", "B"), levels = c("A", "B")),
  A = c(0.8, 0.2, 0.7, 0.3),
  B = c(0.2, 0.8, 0.3, 0.7)
)
multiClassSummary(data)

specmine documentation built on Aug. 5, 2026, 5:06 p.m.