Regression: objectives and metrics

Name Used for optimization User-defined parameters Formula and/or description
MAE +

use_weights

Default: true

Calculation principles

MAPE +

use_weights

Default: true

Calculation principles

Poisson +

Calculation principles

Quantile +

alpha

Default:  0.5

Calculation principles

RMSE +

Calculation principles

LogLinQuantile +

alpha

Default:  0.5

Calculation principles

Lq +

q

Default: Obligatory parameter

Calculation principles

Huber +

Calculation principles

Expectile +

Calculation principles

FairLoss

Calculation principles

NumErrors

greater_than

use_weights

Default: true

The proportion of predictions, for which the difference from the label value exceeds the specified value greater_than.

Calculation principles

SMAPE

use_weights

Default: true

Calculation principles

R2

use_weights

Default: true

Calculation principles

MSLE

use_weights

Default: true

Calculation principles

MedianAbsoluteError

Calculation principles

Name Used for optimization User-defined parameters Formula and/or description
MAE +

use_weights

Default: true

Calculation principles

MAPE +

use_weights

Default: true

Calculation principles

Poisson +

Calculation principles

Quantile +

alpha

Default:  0.5

Calculation principles

RMSE +

Calculation principles

LogLinQuantile +

alpha

Default:  0.5

Calculation principles

Lq +

q

Default: Obligatory parameter

Calculation principles

Huber +

Calculation principles

Expectile +

Calculation principles

FairLoss

Calculation principles

NumErrors

greater_than

use_weights

Default: true

The proportion of predictions, for which the difference from the label value exceeds the specified value greater_than.

Calculation principles

SMAPE

use_weights

Default: true

Calculation principles

R2

use_weights

Default: true

Calculation principles

MSLE

use_weights

Default: true

Calculation principles

MedianAbsoluteError

Calculation principles