mlr3measures (version 0.3.1)

mse: Mean Squared Error

Description

Regression measure defined as $$ \frac{1}{n} \sum_{i=1}^n \left( t_i - r_i \right)^2. $$

Usage

mse(truth, response, ...)

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.

...

(any) Additional arguments. Currently ignored.

Value

Performance value as numeric(1).

Meta Information

• Type: "regr"

• Range: \([0, \infty)\)

• Minimize: TRUE

• Required prediction: response

See Also

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

Examples

# NOT RUN {
set.seed(1)
truth = 1:10
response = truth + rnorm(10)
mse(truth, response)
# }