bias: Bias

In Metrics: Evaluation Metrics for Machine Learning

Description

bias computes the average amount by which actual is greater than predicted.

Usage

bias(actual, predicted)

Arguments

actual	The ground truth numeric vector.
predicted	The predicted numeric vector, where each element in the vector is a prediction for the corresponding element in actual.

Details

If a model is unbiased bias(actual, predicted) should be close to zero. Bias is calculated by taking the average of (actual - predicted).

See Also

percent_bias

Examples

actual <- c(1.1, 1.9, 3.0, 4.4, 5.0, 5.6)
predicted <- c(0.9, 1.8, 2.5, 4.5, 5.0, 6.2)
bias(actual, predicted)

Example output

[1] 0.01666667

Metrics documentation built on May 1, 2019, 10:11 p.m.