The main focus is on preprocessing and data visualization of machine learning models performances. Some functions allow to fill in gaps in time series using linear interpolation on panel data, some functions permit to draw lift effect and lift curve in order to benchmark machine learning models or you can even find the optimal number of clusters in agglomerative clustering algorithm.
| Version: | 1.1.3 |
| Depends: | R (≥ 3.5.0) |
| Imports: | dplyr (≥ 0.7.8), ggplot2 (≥ 3.2.0), sqldf (≥ 0.4-11), stringr (≥ 1.3.1), rlang (≥ 0.4.2), stats (≥ 3.5.0) |
| Suggests: | devtools (≥ 2.2.1), testthat (≥ 2.1.0), covr (≥ 3.4.0) |
| Published: | 2020-06-13 |
| Author: | Simon Corde [aut, cre] |
| Maintainer: | Simon Corde <simon.corde at hotmail.fr> |
| BugReports: | https://github.com/Redcart/helda/issues |
| License: | GPL-3 |
| URL: | https://www.github.com/Redcart/helda |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | helda results |
| Reference manual: | helda.pdf |
| Package source: | helda_1.1.3.tar.gz |
| Windows binaries: | r-devel: helda_1.1.3.zip, r-release: helda_1.1.3.zip, r-oldrel: helda_1.1.3.zip |
| macOS binaries: | r-release: helda_1.1.3.tgz, r-oldrel: helda_1.1.3.tgz |
| Old sources: | helda archive |
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