wbt_svm_classification: Svm classification
In whitebox: 'WhiteboxTools' R Frontend

wbt_svm_classification

R Documentation

Svm classification

Description

Performs an SVM binary classification using training site polygons/points and multiple input images.

Usage

wbt_svm_classification(
  inputs,
  training,
  field,
  scaling = "Normalize",
  output = NULL,
  c = 200,
  gamma = 50,
  tolerance = 0.1,
  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 data.
`scaling`	Scaling method for predictors. Options include 'None', 'Normalize', and 'Standardize'.
`output`	Name of the output raster file.
`c`	c-value, the regularization parameter.
`gamma`	Gamma parameter used in setting the RBF (Gaussian) kernel function.
`tolerance`	The tolerance parameter used in determining the stopping condition.
`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`.