wbt_svm_regression: Svm regression

View source: R/machine_learning.R

wbt_svm_regressionR Documentation

Svm regression

Description

Performs a supervised SVM regression analysis using training site points and predictor rasters.

Usage

wbt_svm_regression(
  inputs,
  training,
  field,
  scaling = "Normalize",
  output = NULL,
  c = 50,
  eps = 10,
  gamma = 0.5,
  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 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.

eps

Epsilon in the epsilon-SVR model.

gamma

Gamma parameter used in setting the RBF (Gaussian) kernel function.

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.


whitebox documentation built on May 29, 2024, 1:21 a.m.