Performs a supervised k-nearest neighbour classification using training site polygons/points and predictor rasters.
wbt_knn_classification(
inputs,
training,
field,
scaling = "Normalize",
output = NULL,
k = 5,
clip = TRUE,
test_proportion = 0.2,
wd = NULL,
verbose_mode = NULL,
compress_rasters = NULL,
command_only = FALSE
)
Returns the tool text outputs.
Names of the input predictor rasters.
Name of the input training site polygons/points shapefile.
Name of the attribute containing class name data.
Scaling method for predictors. Options include 'None', 'Normalize', and 'Standardize'.
Name of the output raster file.
k-parameter, which determines the number of nearest neighbours used.
Perform training data clipping to remove outlier pixels?.
The proportion of the dataset to include in the test split; default is 0.2.
Changes the working directory. Default: NULL
will use the value in WhiteboxTools settings, see wbt_wd()
for details.
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.
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.
Return command that would be executed by system()
rather than running tool. Default: FALSE
.