flightcallr uses the seewave package to generate acoustic measurements ("features") of sounds, and then trains and uses random forest models to make predictions based on these features. Accuracy can be constrained via cross-validation. Convenience functions for reading and writing Raven selection tables are included.
|Author||Jesse C. Ross|
|Date of publication||2013-09-06 18:03:23|
|Maintainer||Jesse C. Ross <firstname.lastname@example.org>|
assess.doneness: assess doneness
bandlimit.spectrum: bandlimit spectrum
calculate.operating.parameters: calculate operating parameters
combined.sparrow.model: A Random Forest model for high-band detections.
combined.thrush.model: A Random Forest model for low-band detections.
danby: Sample NFC Detections
flightcallr-package: Classify Night Flight Calls Based on Acoustic Measurements
generate.forest.predictions: generate forest predictions
generate.seewave.measures: generate seewave measures
nfold.xval: nfold xval
read.selection.table: read selection table
rejigger.perf: rejigger perf
save.selection.table: save selection table
seewave.measures: List of seewave measurements returned by...