An interface to the algorithms of 'Interpretable AI' <https://www.interpretable.ai> from the R programming language. 'Interpretable AI' provides various modules, including 'Optimal Trees' for classification, regression, prescription and survival analysis, 'Optimal Imputation' for missing data imputation and outlier detection, and 'Optimal Feature Selection' for exact sparse regression. The 'iai' package is an open-source project. The 'Interpretable AI' software modules are proprietary products, but free academic and evaluation licenses are available.
| Version: | 1.3.0 |
| Imports: | JuliaCall, stringr, rlang, lifecycle |
| Suggests: | testthat, covr |
| Published: | 2020-08-05 |
| Author: | Jack Dunn [aut, cre], Ying Zhuo [aut], Interpretable AI LLC [cph] |
| Maintainer: | Jack Dunn <jack at interpretable.ai> |
| License: | MIT + file LICENSE |
| URL: | https://www.interpretable.ai |
| NeedsCompilation: | yes |
| SystemRequirements: | Julia (>= 1.0) and Interpretable AI System Image (>= 1.0.0) |
| Materials: | README NEWS |
| In views: | MissingData |
| CRAN checks: | iai results |
| Reference manual: | iai.pdf |
| Package source: | iai_1.3.0.tar.gz |
| Windows binaries: | r-devel: iai_1.3.0.zip, r-release: iai_1.3.0.zip, r-oldrel: iai_1.2.0.zip |
| macOS binaries: | r-release: iai_1.2.0.tgz, r-oldrel: iai_1.3.0.tgz |
| Old sources: | iai archive |
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