Package: AdaSampling 1.3
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>.
Authors:
AdaSampling_1.3.tar.gz
AdaSampling_1.3.zip(r-4.5)AdaSampling_1.3.zip(r-4.4)AdaSampling_1.3.zip(r-4.3)
AdaSampling_1.3.tgz(r-4.4-any)AdaSampling_1.3.tgz(r-4.3-any)
AdaSampling_1.3.tar.gz(r-4.5-noble)AdaSampling_1.3.tar.gz(r-4.4-noble)
AdaSampling_1.3.tgz(r-4.4-emscripten)AdaSampling_1.3.tgz(r-4.3-emscripten)
AdaSampling.pdf |AdaSampling.html✨
AdaSampling/json (API)
| # Install 'AdaSampling' in R: |
| install.packages('AdaSampling', repos = c('https://pyanglab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pengyiyang/adasampling/issues
- brca - Wisconsin Breast Cancer Database
Last updated 6 years agofrom:c815f1bf8d. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 08 2024 |
| R-4.5-win | OK | Nov 08 2024 |
| R-4.5-linux | OK | Nov 08 2024 |
| R-4.4-win | OK | Nov 08 2024 |
| R-4.4-mac | OK | Nov 08 2024 |
| R-4.3-win | OK | Nov 08 2024 |
| R-4.3-mac | OK | Nov 08 2024 |
Exports:adaSampleadaSvmBenchmarksingleIterweightedKNN
Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
