whitebox (version 2.1.0)

wbt_svm_classification: 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 = FALSE,
  compress_rasters = 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.

verbose_mode

Sets verbose mode. If verbose mode is False, tools will not print output messages.

compress_rasters

Sets the flag used by WhiteboxTools to determine whether to use compression for output rasters.

Value

Returns the tool text outputs.