Component-wise gradient boosting learner

A Learner for a component-wise boosting model implemented in Compboost.

Super class

mlr3::Learner -> LearnerCompboost

Methods

Public methods

• LearnerCompboost$new()

• LearnerCompboost$importance()

• LearnerCompboost$selected_features()

• LearnerCompboost$save_json()

• LearnerCompboost$clone()

Inherited methods

• mlr3::Learner$base_learner()
• mlr3::Learner$format()
• mlr3::Learner$help()
• mlr3::Learner$predict()
• mlr3::Learner$predict_newdata()
• mlr3::Learner$print()
• mlr3::Learner$reset()
• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerCompboost$new(ttype)

Arguments

ttype

(character(1))
The task type of the learner. Must be regr or classif.

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Method importance()

The importance scores are extracted from the model slot $calculateFEatureImportance().

Usage

LearnerCompboost$importance()

Returns

Named numeric().

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Method selected_features()

Selected features are extracted from the model slot $getSelectedBaselearner().

Usage

LearnerCompboost$selected_features()

Returns

character().

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Method save_json()

Save the model to a JSON file.

Usage

LearnerCompboost$save_json(file)

Arguments

file

(character(1)
Name/path to the file.

Returns

character(1)

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerCompboost$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.