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

## 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`

.- sample_weights
(

`numeric()`

)

Vector of non-negative and finite sample weights. Must have the same length as`truth`

. The vector gets automatically normalized to sum to one. Defaults to equal sample weights.- ...
(

`any`

)

Additional arguments. Currently ignored.

## Details

The Mean Squared Error is defined as $$ \frac{1}{n} \sum_{i=1}^n w_i \left( t_i - r_i \right)^2, $$ where \(w_i\) are normalized sample weights.