TLBC: Two-Level Behavior Classification

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. Includes functions for training a two-level model, applying the model to data, and computing performance.

Version: 1.0
Depends: R (≥ 2.10)
Imports: stringr, randomForest, HMM, tools, signal, caret
Published: 2015-10-14
Author: Katherine Ellis
Maintainer: Katherine Ellis <kellis at ucsd.edu>
BugReports: NA
License: GPL-2
URL: NA
NeedsCompilation: no
Materials: README
CRAN checks: TLBC results

Downloads:

Reference manual: TLBC.pdf
Package source: TLBC_1.0.tar.gz
Windows binaries: r-devel: TLBC_1.0.zip, r-release: TLBC_1.0.zip, r-oldrel: TLBC_1.0.zip
OS X Mavericks binaries: r-release: TLBC_1.0.tgz, r-oldrel: TLBC_1.0.tgz