FSelectorSequential
class that implements sequential feature selection. The
sequential forward selection (strategy = fsf
) extends the feature set in
each step with the feature that increases the models performance the most.
The sequential backward selection (strategy = fsb
) starts with the complete
future set and removes in each step the feature that decreases the models
performance the least.
Feature sets are evaluated in batches, where each batch is one step in the sequential feature selection.
This FSelector can be instantiated via the dictionary
mlr_fselectors or with the associated sugar function fs()
:
mlr_fselectors$get("sequential") fs("sequential")
max_features
integer(1)
Maximum number of features. By default, number of features in mlr3::Task.
strategy
character(1)
Search method sfs
(forward search) or sbs
(backward search).
mlr3fselect::FSelector
-> FSelectorSequential
new()
Creates a new instance of this R6 class.`
FSelectorSequential$new()
optimization_path()
Returns the optimization path.
FSelectorSequential$optimization_path(inst)
inst
(FSelectInstanceSingleCrit)
Instance optimized with FSelectorSequential.
clone()
The objects of this class are cloneable with this method.
FSelectorSequential$clone(deep = FALSE)
deep
Whether to make a deep clone.