mtr_explained_variance: Explained Variance
In chuvanan/metrics: Metrics For Evaluating Machine Learning Models

Description Usage Arguments Value Author(s) See Also Examples

mtr_explained_variance computes explained variance, also known as explained variation, which is interpreted as the percentage of variation in one numeric vector explained by another. The best possible score is 1.0, lower values are worse.

1	mtr_explained_variance(actual, predicted)

`actual`	`[numeric]` The ground truth numeric vector.
`predicted`	`[numeric]` The predicted numeric vector, where each element in the vector is a prediction of the corresponding elements in `actual`.

A numeric scalar output

An Chu

mtr_r2

act <- c(3, -0.5, 2, 7)
pred <- c(2.5, 0.0, 2, 8)
mtr_explained_variance(act, pred)

act <- c(1.1, 1.9, 3.0, 4.4, 5.0, 5.6)
pred <- c(0.9, 1.8, 2.5, 4.5, 5.0, 6.2)
mtr_explained_variance(act, pred)