K means clustering — wbt_k_means_clustering • whitebox

Performs a k-means clustering operation on a multi-spectral dataset.

Usage

wbt_k_means_clustering(
  inputs,
  output,
  classes,
  out_html = NULL,
  max_iterations = 10,
  class_change = 2,
  initialize = "diagonal",
  min_class_size = 10,
  wd = NULL,
  verbose_mode = NULL,
  compress_rasters = NULL,
  command_only = FALSE
)

Arguments

inputs: Input raster file paths, concatenated with "," or ";". See wbt_file_path() for details.
output: Output raster file.
classes: Number of classes.
out_html: Output HTML report file.
max_iterations: Maximum number of iterations.
class_change: Minimum percent of cells changed between iterations before completion.
initialize: How to initialize cluster centres?.
min_class_size: Minimum class size, in pixels.
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.