Package: banter 0.9.6

banter:BioAcoustic eveNT classifiER

Create a hierarchical acoustic event species classifier out of multiple call type detectors as described in Rankin et al (2017) <doi:10.1111/mms.12381>.

Authors:Eric Archer [aut, cre], Taiki Sakai [aut]

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banter.pdf |banter.html✨
banter/json (API)

# Installbanter in R:

install.packages('banter', repos = c('https://ericarcher.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ericarcher/banter/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

test.data - Testing events and detectors
train.data - Training events and detectors

On CRAN:

acoustics bioacoustics cetaceans classification dolphins machine-learning noaa random-forest species-identification supervised-learning supervised-machine-learning whales

17 exports 9 stars 1.53 score 76 dependencies 238 downloads

Last updated 6 months agofrom:bc102cb457

Exports:addBanterDetector banterGuide getBanterModel getBanterModelData getDetectorNames getSampSize initBanterModel modelPctCorrect numCalls numEvents plotDetectorTrace predict propCalls removeBanterDetector runBanterModel subsampleDetections summary

Dependencies:abind class classInt cli clue cluster coda colorspace cpp11 DBI deldir dplyr e1071 fansi farver fBasics generics ggplot2 ggrepel glue gridExtra gss gtable HDInterval igraph isoband KernSmooth kknn labeling lattice lifecycle magrittr MASS Matrix mgcv modeest munsell nlme pillar pkgconfig polyclip proxy purrr R6 randomForest RColorBrewer Rcpp rfPermute rlang rmutil rpart runjags s2 scales sf spatial spatstat.data spatstat.geom spatstat.utils stable stabledist statip stringi stringr swfscMisc tibble tidyr tidyselect timeDate timeSeries units utf8 vctrs viridisLite withr wk

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
BioAcoustic EveNT ClassifiER	banter-package banter
Add a BANTER Detector Model	addBanterDetector removeBanterDetector
BANTER Guide	banterGuide
Extract Random Forest Model	getBanterModel
Extract Random Forest Model Data	getBanterModelData
Detector Names	getDetectorNames
Sample Size	getSampSize
Initialize BANTER model	initBanterModel
Model Percent Correct	modelPctCorrect
Number and Proportion of Calls	numCalls propCalls
Number of Events	numEvents
Plot BANTER Detector Traces	plotDetectorTrace
Predict BANTER events	predict predict,banter_model-method predict.banter_model
Run BANTER Model	runBanterModel
Subsample Detections	subsampleDetections
BANTER Classifier Model Summary	summary summary,banter_model-method summary.banter_model
Testing events and detectors	test.data
Training events and detectors	train.data