Package: sansa 0.0.1

Murtaza Nasir

sansa: Synthetic Data Generation for Imbalanced Learning in 'R'

Machine learning is widely used in information-systems design. Yet, training algorithms on imbalanced datasets may severely affect performance on unseen data. For example, in some cases in healthcare, financial, or internet-security contexts, certain sub-classes are difficult to learn because they are underrepresented in training data. This 'R' package offers a flexible and efficient solution based on a new synthetic average neighborhood sampling algorithm ('SANSA'), which, in contrast to other solutions, introduces a novel “placement” parameter that can be tuned to adapt to each datasets unique manifestation of the imbalance. More information about the algorithm's parameters can be found at Nasir et al. (2022) <https://murtaza.cc/SANSA/>.

Authors:Murtaza Nasir [aut, cre], Ali Dag [ctb], Serhat Simsek [ctb], Anton Ivanov [ctb], Asil Oztekin [ths]

sansa_0.0.1.tar.gz
sansa_0.0.1.tar.gz(r-4.5-noble)sansa_0.0.1.tar.gz(r-4.4-noble)
sansa_0.0.1.tgz(r-4.4-emscripten)sansa_0.0.1.tgz(r-4.3-emscripten)
sansa.pdf |sansa.html
sansa/json (API)

# Install 'sansa' in R:
install.packages('sansa', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 4 scripts 232 downloads 1 exports 30 dependencies

Last updated 2 years agofrom:6f37a16592. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-linuxOKNov 12 2024

Exports:sansa

Dependencies:clicolorspacedata.tablefansifarverFNNggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr