Measure to compare true observed response with predicted response in regression tasks.

## Usage

rsq(truth, response, na_value = NaN, ...)

## Arguments

truth

(numeric())
True (observed) values. Must have the same length as response.

response

(numeric())
Predicted response values. Must have the same length as truth.

na_value

(numeric(1))
Value that should be returned if the measure is not defined for the input (as described in the note). Default is NaN.

...

(any)
Additional arguments. Currently ignored.

## Value

Performance value as numeric(1).

## Details

R Squared is defined as $$1 - \frac{\sum_{i=1}^n \left( t_i - r_i \right)^2}{\sum_{i=1}^n \left( t_i - \bar{t} \right)^2}.$$ Also known as coefficient of determination or explained variation. Subtracts the rse() from 1, hence it compares the squared error of the predictions relative to a naive model predicting the mean.

This measure is undefined for constant $$t$$.

## Meta Information

• Type: "regr"

• Range: $$(-\infty, 1]$$

• Minimize: FALSE

• Required prediction: response

Other Regression Measures: ae(), ape(), bias(), ktau(), mae(), mape(), maxae(), maxse(), medae(), medse(), mse(), msle(), pbias(), rae(), rmse(), rmsle(), rrse(), rse(), sae(), se(), sle(), smape(), srho(), sse()
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