onesvm: Identify outliers using One Class Support Vector Machines

In specleanr: Detecting Environmental Outliers in Data Analysis Pipelines

Identify outliers using One Class Support Vector Machines

Description

Identify outliers using One Class Support Vector Machines

Usage

onesvm(
  data,
  kernel = "radial",
  tune = FALSE,
  exclude = NULL,
  output,
  tpar = list(gamma = 1^(-1:1), epislon = seq(0, 1, 0.1), cost = 2^2:4, nu = seq(0.05, 1,
    0.1)),
  boot = FALSE,
  pc = FALSE,
  var,
  pcvar = NULL
)

Arguments

data	Dataframe of environmental variables extracted from where the species was recorded present or absent.
kernel	Either radial, linear
tune	To performed a tuned version of one-class svm. High computation requirements needed.
exclude	Exclude variables that should not be considered in the fitting the one class model, for example x and y columns or latitude/longitude or any column that the user doesnot want to consider.
output	Either clean: for a dataset with no outliers or outlier: to output a dataframe with outliers.
tpar	A list of parameters to be varied during tunning from the normal model.
boot	Whether bootstrapping will be computed. Default FALSE
pc	Whether principal component analysis will be computed. Default FALSE
var	The variable of concern, which is vital for univariate outlier detection methods
pcvar	Principal component analysis to e used for outlier detection after PCA. Default PC1

Value

Dataframe with or with no outliers.

Examples

data("efidata")

danube <- system.file('extdata/danube.shp.zip', package='specleanr')

db <- sf::st_read(danube, quiet=TRUE)

wcd <- terra::rast(system.file('extdata/worldclim.tiff', package='specleanr'))

refdata <- pred_extract(data = efidata, raster= wcd ,
                       lat = 'decimalLatitude',
                       lon= 'decimalLongitude',
                       colsp = "scientificName",
                      bbox = db,
                       minpts = 10)

nedata <- onesvm(data = refdata[["Thymallus thymallus"]], exclude = c("x", "y"),  output='outlier')

specleanr documentation built on Nov. 26, 2025, 1:07 a.m.