Density Locfit Learner
mlr_learners_dens.locfit.Rd
Local density estimation.
Calls locfit::density.lf()
from locfit.
Dictionary
This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn()
:
$get("dens.locfit")
mlr_learnerslrn("dens.locfit")
Meta Information
Task type: “dens”
Predict Types: “pdf”
Feature Types: “integer”, “numeric”
Required Packages: mlr3, mlr3proba, mlr3extralearners, locfit
Parameters
Id | Type | Default | Levels | Range |
window | character | gaus | tcub, rect, trwt, tria, epan, bisq, gaus | - |
width | numeric | - | \((-\infty, \infty)\) | |
from | numeric | - | \((-\infty, \infty)\) | |
to | numeric | - | \((-\infty, \infty)\) | |
cut | numeric | - | \((-\infty, \infty)\) | |
deg | numeric | 0 | \((-\infty, \infty)\) | |
link | character | ident | ident, log, logit, inverse, sqrt, arcsin | - |
kern | character | tcub | rect, trwt, tria, epan, bisq, gauss, tcub | - |
kt | character | sph | sph, prod | - |
renorm | logical | FALSE | TRUE, FALSE | - |
maxk | integer | 100 | \([0, \infty)\) | |
itype | character | - | prod, mult, mlin, haz | - |
mint | integer | 20 | \([1, \infty)\) | |
maxit | integer | 20 | \([1, \infty)\) |
References
Loader, Clive (2006). Local regression and likelihood. Springer Science & Business Media.
See also
as.data.table(mlr_learners)
for a table of available Learners in the running session (depending on the loaded packages).Chapter in the mlr3book: https://mlr3book.mlr-org.com/basics.html#learners
mlr3learners for a selection of recommended learners.
mlr3cluster for unsupervised clustering learners.
mlr3pipelines to combine learners with pre- and postprocessing steps.
mlr3tuning for tuning of hyperparameters, mlr3tuningspaces for established default tuning spaces.
Super classes
mlr3::Learner
-> mlr3proba::LearnerDens
-> LearnerDensLocfit
Examples
learner = mlr3::lrn("dens.locfit")
print(learner)
#> <LearnerDensLocfit:dens.locfit>: Local Density Estimation
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3proba, mlr3extralearners, locfit
#> * Predict Types: [pdf]
#> * Feature Types: integer, numeric
#> * Properties: -
# available parameters:
learner$param_set$ids()
#> [1] "window" "width" "from" "to" "cut" "deg" "link" "kern"
#> [9] "kt" "renorm" "maxk" "itype" "mint" "maxit"