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> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | TLBC results |
| 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 |
| macOS binaries: | r-release: TLBC_1.0.tgz, r-oldrel: TLBC_1.0.tgz |
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