Knn classification — wbt_knn_classification • whitebox

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.

Value

Returns the tool text outputs.