wbt_knn_classification: Knn classification
In whitebox: 'WhiteboxTools' R Frontend

wbt_knn_classification

R Documentation

Knn classification

Description

Performs a supervised k-nearest neighbour classification using training site polygons/points and predictor rasters.

Usage

wbt_knn_classification(
  inputs,
  training,
  field,
  scaling = "Normalize",
  output = NULL,
  k = 5,
  clip = TRUE,
  test_proportion = 0.2,
  wd = NULL,
  verbose_mode = NULL,
  compress_rasters = NULL,
  command_only = FALSE
)

Arguments

`inputs`	Names of the input predictor rasters.
`training`	Name of the input training site polygons/points shapefile.
`field`	Name of the attribute containing class name data.
`scaling`	Scaling method for predictors. Options include 'None', 'Normalize', and 'Standardize'.
`output`	Name of the output raster file.
`k`	k-parameter, which determines the number of nearest neighbours used.
`clip`	Perform training data clipping to remove outlier pixels?.
`test_proportion`	The proportion of the dataset to include in the test split; default is 0.2.
`wd`	Changes the working directory. Default: `NULL` will use the value in WhiteboxTools settings, see `wbt_wd()` for details.
`verbose_mode`	Sets verbose mode. If verbose mode is `FALSE`, tools will not print output messages. Default: `NULL` will use the value in WhiteboxTools settings, see `wbt_verbose()` for details.
`compress_rasters`	Sets the flag used by 'WhiteboxTools' to determine whether to use compression for output rasters. Default: `NULL` will use the value in WhiteboxTools settings, see `wbt_compress_rasters()` for details.
`command_only`	Return command that would be executed by `system()` rather than running tool. Default: `FALSE`.