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Contrast trees represent a new approach for assessing the accuracy of many types of machine learning estimates that are not amenable to standard (cross) validation methods; see "Contrast trees and distribution boosting", Jerome H. Friedman (2020) <doi:10.1073/pnas.1921562117>. In situations where inaccuracies are detected, boosted contrast trees can often improve performance. Functions are provided to to build such trees in addition to a special case, distribution boosting, an assumption free method for estimating the full probability distribution of an outcome variable given any set of joint input predictor variable values.
| Version: | 0.3-1 |
| Depends: | R (≥ 3.5) |
| Imports: | stats, graphics |
| Suggests: | randomForest, knitr, rmarkdown |
| Published: | 2023-11-22 |
| Author: | Jerome Friedman [aut, cph], Balasubramanian Narasimhan [aut, cre] |
| Maintainer: | Balasubramanian Narasimhan <naras at stanford.edu> |
| BugReports: | https://github.com/bnaras/conTree/issues |
| License: | Apache License 2.0 |
| URL: | https://jhfhub.github.io/conTree_tutorial/ |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | conTree results |
| Reference manual: | conTree.pdf |
| Vignettes: |
conTree |
| Package source: | conTree_0.3-1.tar.gz |
| Windows binaries: | r-devel: conTree_0.3-1.zip, r-release: conTree_0.3-1.zip, r-oldrel: conTree_0.3-1.zip |
| macOS binaries: | r-release (arm64): conTree_0.3-1.tgz, r-oldrel (arm64): conTree_0.3-1.tgz, r-release (x86_64): conTree_0.3-1.tgz, r-oldrel (x86_64): conTree_0.3-1.tgz |
| Old sources: | conTree archive |
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