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pheble: Classifying High-Dimensional Phenotypes with Ensemble Learning

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

Documentation:

Reference manual: pheble.pdf

Downloads:

Package source: pheble_0.1.0.tar.gz
Windows binaries: r-devel: pheble_0.1.0.zip, r-release: pheble_0.1.0.zip, r-oldrel: pheble_0.1.0.zip
macOS binaries: r-release (arm64): pheble_0.1.0.tgz, r-oldrel (arm64): pheble_0.1.0.tgz, r-release (x86_64): pheble_0.1.0.tgz, r-oldrel (x86_64): pheble_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.