Instantiates an AuditorFitter that trains a mlr3::Learner on the data.

Value

AuditorFitter

list with items

  • corr: pseudo-correlation between residuals and learner prediction.

  • l: the trained learner.

Functions

  • TreeAuditorFitter: Learner auditor based on rpart

  • RidgeAuditorFitter: Learner auditor based on glmnet

Super class

mcboost::AuditorFitter -> LearnerAuditorFitter

Public fields

learner

LearnerPredictor
Learner used for fitting residuals.

Methods

Inherited methods


Method new()

Define an AuditorFitter from a Learner. Available instantiations:
TreeAuditorFitter (rpart) and RidgeAuditorFitter (glmnet).

Usage

Arguments

learner

mlr3::Learner
Regression learner to use.


Method fit()

Fit the learner and compute correlation

Usage

LearnerAuditorFitter$fit(data, resid, mask)

Arguments

data

data.table
Features.

resid

numeric
Residuals (of same length as data).

mask

integer
Mask applied to the data. Only used for SubgroupAuditorFitter.


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerAuditorFitter$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Super classes

mcboost::AuditorFitter -> mcboost::LearnerAuditorFitter -> TreeAuditorFitter

Methods

Inherited methods


Method new()

Define a AuditorFitter from a rpart learner.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

TreeAuditorFitter$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Super classes

mcboost::AuditorFitter -> mcboost::LearnerAuditorFitter -> RidgeAuditorFitter

Methods

Inherited methods


Method new()

Define a AuditorFitter from a glmnet learner.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

RidgeAuditorFitter$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.