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Implements the adaptive sampling procedure, a framework for both positive unlabeled learning and learning with class label noise. Yang, P., Ormerod, J., Liu, W., Ma, C., Zomaya, A., Yang, J. (2018) <doi:10.1109/TCYB.2018.2816984>.
Version: | 1.3 |
Depends: | R (≥ 3.4.0) |
Imports: | caret (≥ 6.0-78) , class (≥ 7.3-14), e1071 (≥ 1.6-8), stats, MASS |
Suggests: | knitr, rmarkdown |
Published: | 2019-05-21 |
DOI: | 10.32614/CRAN.package.AdaSampling |
Author: | Pengyi Yang |
Maintainer: | Pengyi Yang <yangpy7 at gmail.com> |
BugReports: | https://github.com/PengyiYang/AdaSampling/issues |
License: | GPL-3 |
URL: | https://github.com/PengyiYang/AdaSampling/ |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | AdaSampling results |
Reference manual: | AdaSampling.pdf |
Vignettes: |
Breast cancer classification with AdaSampling |
Package source: | AdaSampling_1.3.tar.gz |
Windows binaries: | r-devel: AdaSampling_1.3.zip, r-release: AdaSampling_1.3.zip, r-oldrel: AdaSampling_1.3.zip |
macOS binaries: | r-release (arm64): AdaSampling_1.3.tgz, r-oldrel (arm64): AdaSampling_1.3.tgz, r-release (x86_64): AdaSampling_1.3.tgz, r-oldrel (x86_64): AdaSampling_1.3.tgz |
Old sources: | AdaSampling archive |
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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.