KERREG: Kernel Regression

In fdm2id: Data Mining and R Programming for Beginners

Kernel Regression

Description

This function builds a kernel regression model.

Usage

KERREG(
  x,
  y,
  bandwidth = 1,
  tune = FALSE,
  methodparameters = NULL,
  graph = FALSE,
  seed = NULL,
  ...
)

Arguments

x	Predictor matrix.
y	Response vector.
bandwidth	The bandwidth parameter.
tune	If true, the function returns parameters instead of a classification model.
methodparameters	Present for interface consistency with performance (which always passes it when fitting a model). Currently unused: KERREG does not support reusing pre-tuned parameters.
graph	Present for interface consistency with performance (which always passes it when fitting a model). Currently unused: KERREG does not produce a plot.
seed	A specified seed for random number generation, so that two runs on the same data give the same model. Every learning method accepts it, so that it can be set the same way whatever the method; the deterministic ones simply have nothing to draw and give the same model with or without it.
...	Other parameters.

Value

The classification model, as an object of class model-class.

See Also

npregress

Examples

require (datasets)
data (trees)
KERREG (trees [, -3], trees [, 3])

fdm2id documentation built on Aug. 28, 2026, 9:07 a.m.