Description Details Author(s) See Also Examples
Contains functions for training and applying two-level random forest and hidden Markov models for human behavior classification from raw tri-axial accelerometer and/or GPS data.
This code works with csv data from Actigraph accelerometers (please export in RAW format, without timestamps), and/or with GPS data processed by the PALMS GPS cleaning software.
The TLBC classifier uses six behavior labels:
Sitting
Standing Still
Standing Moving
Walking/Running
Bicycling
Vehicle
Function classify
uses a pre-learned TLBC model to classify accelerometer and/or GPS data with behavior labels. Pre-trained models that have been trained on three UCSD datasets are available for download.
Function trainModel
trains a TLBC model from annotated accelerometer and/or GPS data.
Function calcPerformance
computes the accuracy of predictions made on a given dataset.
Function looXval
performs leave-one-out cross-validation on a dataset.
Package: | TLBC |
Type: | Package |
Version: | 1.0 |
Date: | 2015-05-29 |
License: | GPL-2 |
Katherine Ellis <kellis@ucsd.edu>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | ## Not run:
# train a new model
myAnnotations="~/myStudy/annotations.csv"
myAccel="~/myStudy/HipGT3X+"
myGPS="~/myStudy/GPS.csv"
WS=60
myModel="~/myStudy/myModel.RData"
trainModel(annotations=myAnnotations, accelerometers=myAccel, GPS=myGPS, winSize=WS,
modelName=myModel)
# classify using a model computed yourself
myAccel="~/myStudy/HipGT3X+"
myGPS="~/myStudy/GPS.csv"
myModel="~/myStudy/myModel.RData"
myPredictions="~/myStudy/myModelPredictions"
classify(accelerometers=myAccel, GPS=myGPS, modelName=myModel, saveDir=myPredictions)
# compute the performance of a model on a dataset
myAnnotations="~/myStudy/annotations.csv"
myPredictions="~/myStudy/myModelPredictions"
WS=60
calcPerformance(annotations=myAnnotations, predictions=myPredictions, winSize=WS)
# perform leave-one-out cross-validation on a dataset
myAnnotations="~/myStudy/annotations.csv"
myAccel="~/myStudy/HipGT3X+"
WS=60
myPredictions="~/myStudy/looXvalPredictions"
looXval(annotations=myAnnotations, accelerometers=myAccel, winSize=WS, saveDir=myPredictions)
## End(Not run)
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