wbt_random_forest_regression: Random forest regression

View source: R/machine_learning.R

wbt_random_forest_regressionR Documentation

Random forest regression

Description

Performs a random forest regression analysis using training site data and predictor rasters.

Usage

wbt_random_forest_regression(
  inputs,
  training,
  field,
  output = NULL,
  n_trees = 100,
  min_samples_leaf = 1,
  min_samples_split = 2,
  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 response variable name data.

output

Name of the output raster file. This parameter is optional. When unspecified, the tool will only build the model. When specified, the tool will use the built model and predictor rasters to perform a spatial prediction.

n_trees

The number of trees in the forest.

min_samples_leaf

The minimum number of samples required to be at a leaf node.

min_samples_split

The minimum number of samples required to split an internal node.

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.