eclust: Environment Based Clustering for Interpretable Predictive Models
in High Dimensional Data
Companion package to the paper: An analytic approach for
interpretable predictive models in high dimensional data, in the presence of
interactions with exposures. Bhatnagar, Yang, Khundrakpam, Evans, Blanchette, Bouchard, Greenwood (2017) <doi:10.1101/102475>.
This package includes an algorithm for clustering high dimensional data that can be affected by an environmental factor.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.3.1) |
| Imports: |
caret, data.table, dynamicTreeCut, magrittr, pacman, WGCNA, stringr, pander, stats |
| Suggests: |
cluster, earth, ncvreg, knitr, rmarkdown, protoclust, factoextra, ComplexHeatmap, circlize, pheatmap, viridis, pROC, glmnet |
| Published: |
2017-01-26 |
| DOI: |
10.32614/CRAN.package.eclust |
| Author: |
Sahir Rai Bhatnagar [aut, cre] (http://sahirbhatnagar.com/) |
| Maintainer: |
Sahir Rai Bhatnagar <sahir.bhatnagar at gmail.com> |
| BugReports: |
https://github.com/sahirbhatnagar/eclust/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/sahirbhatnagar/eclust/,
http://sahirbhatnagar.com/eclust/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
eclust results |
Documentation:
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