View source: R/addBanterDetector.R
addBanterDetector | R Documentation |
Add a detector model to a BANTER classifier.
addBanterDetector( x, data, name, ntree, sampsize = 1, importance = FALSE, num.cores = 1 ) removeBanterDetector(x, name)
x |
a |
data |
detector data.frame or named list of detector data.frames. If
a data.frame, then |
name |
detector name. |
ntree |
number of trees. |
sampsize |
number or fraction of samples to use in each tree. If < 1, then it will be used to select this fraction of the smallest sample size. |
importance |
retain importance scores in model? Defaults to
|
num.cores |
number of cores to use for Random Forest model. Set to
|
a banter_model
object with the detector model added or
removed.
Eric Archer eric.archer@noaa.gov
Rankin, S., Archer, F., Keating, J. L., Oswald, J. N., Oswald, M. , Curtis, A. and Barlow, J. (2017), Acoustic classification of dolphins in the California Current using whistles, echolocation clicks, and burst pulses. Marine Mammal Science 33:520-540. doi:10.1111/mms.12381
data(train.data) # initialize BANTER model with event data bant.mdl <- initBanterModel(train.data$events) # add the 'bp' (burst pulse) detector model bant.mdl <- addBanterDetector( x = bant.mdl, data = train.data$detectors$bp, name = "bp", ntree = 50, sampsize = 1, num.cores = 1 ) bant.mdl # remove the 'bp' detector model bant.mdl <- removeBanterDetector(bant.mdl, "bp") bant.mdl
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