Brier: Brier score

In measures: Performance Measures for Statistical Learning

Description

The Brier score is defined as the quadratic difference between the probability and the value (1,0) for the class. That means we use the numeric representation 1 and 0 for our target classes. It is similiar to the mean squared error in regression. multiclass.brier is the sum over all one vs. all comparisons and for a binary classifcation 2 * brier.

Usage

Brier(probabilities, truth, negative, positive)

Arguments

probabilities	[numeric] vector of predicted probabilities
truth	vector of true values
negative	negative class
positive	positive class

Examples

n = 20
set.seed(125)
truth = as.factor(sample(c(1,0), n, replace = TRUE))
probabilities = runif(n)
response = as.factor(as.numeric(probabilities > 0.5))
positive = 1
negative = 0
Brier(probabilities, truth, negative, positive)

Example output

[1] 0.4258912

measures documentation built on Jan. 19, 2021, 5:08 p.m.