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Instance based algorithm: K-nearest neighbours regression. Calls RWeka::IBk() from RWeka.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("regr.IBk")
lrn("regr.IBk")

Meta Information

  • Task type: “regr”

  • Predict Types: “response”

  • Feature Types: “integer”, “numeric”, “factor”, “ordered”

  • Required Packages: mlr3, mlr3extralearners, RWeka

Parameters

IdTypeDefaultLevelsRange
subsetuntyped--
na.actionuntyped--
IlogicalFALSETRUE, FALSE-
FlogicalFALSETRUE, FALSE-
Kinteger1\([1, \infty)\)
ElogicalFALSETRUE, FALSE-
Winteger0\([0, \infty)\)
XlogicalFALSETRUE, FALSE-
Auntypedweka.core.neighboursearch.LinearNNSearch-
output_debug_infologicalFALSETRUE, FALSE-
do_not_check_capabilitieslogicalFALSETRUE, FALSE-
num_decimal_placesinteger2\([1, \infty)\)
batch_sizeinteger100\([1, \infty)\)
optionsuntyped-

Parameter Changes

  • output_debug_info:

    • original id: output-debug-info

  • do_not_check_capabilities:

    • original id: do-not-check-capabilities

  • num_decimal_places:

    • original id: num-decimal-places

  • batch_size:

    • original id: batch-size

  • Reason for change: This learner contains changed ids of the following control arguments since their ids contain irregular pattern

References

Aha, W D, Kibler, Dennis, Albert, K M (1991). “Instance-based learning algorithms.” Machine learning, 6(1), 37--66.

See also

Author

henrifnk

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrIBk

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrIBk$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("regr.IBk")
print(learner)
#> <LearnerRegrIBk:regr.IBk>: K-nearest neighbour
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, RWeka
#> * Predict Type: response
#> * Feature types: numeric, factor, ordered, integer
#> * Properties: -

# available parameters:
learner$param_set$ids()
#>  [1] "subset"                    "na.action"                
#>  [3] "I"                         "F"                        
#>  [5] "K"                         "E"                        
#>  [7] "W"                         "X"                        
#>  [9] "A"                         "output_debug_info"        
#> [11] "do_not_check_capabilities" "num_decimal_places"       
#> [13] "batch_size"                "options"