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CRAN: Package AdaSampling

AdaSampling: Adaptive Sampling for Positive Unlabeled and Label Noise Learning

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 Documentation: Reference manual: AdaSampling.pdf Vignettes: Breast cancer classification with AdaSampling (source, R code)
Downloads: 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 Linking:

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