wbt_knn_regression: Knn regression

View source: R/machine_learning.R

wbt_knn_regressionR Documentation

Knn regression

Description

Performs a supervised k-nearest neighbour regression using training site points and predictor rasters.

Usage

wbt_knn_regression(
  inputs,
  training,
  field,
  scaling = "Normalize",
  output = NULL,
  k = 5,
  weight = TRUE,
  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.

scaling

Scaling method for predictors. Options include 'None', 'Normalize', and 'Standardize'.

output

Name of the output raster file.

k

k-parameter, which determines the number of nearest neighbours used.

weight

Use distance weighting?.

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.


giswqs/whiteboxR documentation built on Oct. 14, 2024, 2:38 a.m.