A system for binary and multi-class classification of
high-dimensional phenotypic data using ensemble learning. By combining
predictions from different classification models, this package attempts
to improve performance over individual learners. The pre-processing,
training, validation, and testing are performed end-to-end to minimize
user input and simplify the process of classification.
| Version: |
0.1.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
adabag, base, C50, caret, caTools, data.table, doParallel, dplyr, e1071, earth, evtree, frbs, glmnet, gmodels, hda, HDclassif, ipred, kernlab, kknn, klaR, magrittr, MASS, Matrix, mda, MLmetrics, nnet, parallel, party, pls, randomForest, rpartScore, sparseLDA, stats, themis, utils |
| Suggests: |
h2o |
| Published: |
2023-05-17 |
| DOI: |
10.32614/CRAN.package.pheble |
| Author: |
Jay Devine [aut, cre, cph],
Bened'ikt Hallgrimsson [aut] |
| Maintainer: |
Jay Devine <jay.devine1 at ucalgary.ca> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| Citation: |
pheble citation info |
| Materials: |
README NEWS |
| CRAN checks: |
pheble results |