Package: accSDA 1.1.3
accSDA: Accelerated Sparse Discriminant Analysis
Implementation of sparse linear discriminant analysis, which is a supervised classification method for multiple classes. Various novel optimization approaches to this problem are implemented including alternating direction method of multipliers ('ADMM'), proximal gradient (PG) and accelerated proximal gradient ('APG') (See Atkins 'et al'. <arxiv:1705.07194>). Functions for performing cross validation are also supplied along with basic prediction and plotting functions. Sparse zero variance discriminant analysis ('SZVD') is also included in the package (See Ames and Hong, <arxiv:1401.5492>). See the 'github' wiki for a more extended description.
Authors:
accSDA_1.1.3.tar.gz
accSDA_1.1.3.zip(r-4.5)accSDA_1.1.3.zip(r-4.4)accSDA_1.1.3.zip(r-4.3)
accSDA_1.1.3.tgz(r-4.4-any)accSDA_1.1.3.tgz(r-4.3-any)
accSDA_1.1.3.tar.gz(r-4.5-noble)accSDA_1.1.3.tar.gz(r-4.4-noble)
accSDA_1.1.3.tgz(r-4.4-emscripten)accSDA_1.1.3.tgz(r-4.3-emscripten)
accSDA.pdf |accSDA.html✨
accSDA/json (API)
NEWS
| # Install 'accSDA' in R: |
| install.packages('accSDA', repos = c('https://gumeo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gumeo/accsda/issues
Last updated 1 years agofrom:b58116b0b4. Checks:7 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 23 2025 |
| R-4.5-win | OK | Jan 23 2025 |
| R-4.5-linux | OK | Jan 23 2025 |
| R-4.4-win | OK | Jan 23 2025 |
| R-4.4-mac | OK | Jan 23 2025 |
| R-4.3-win | OK | Jan 23 2025 |
| R-4.3-mac | OK | Jan 23 2025 |
Exports:ASDAASDABarPlotgenDatnormalizenormalizetestordASDASZVDSZVD_kFold_cvSZVDcvZVD
Dependencies:clicolorspacefansifarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| accSDA: A package for performing sparse discriminant analysis in various ways. | accSDA |
| Accelerated Sparse Discriminant Analysis | ASDA ASDA.default |
| barplot for ASDA objects | ASDABarPlot |
| Generate data for ordinal examples in the package | genDat |
| Normalize training data | normalize |
| Normalize training data | normalizetest |
| Ordinal Accelerated Sparse Discriminant Analysis | ordASDA ordASDA.default |
| Predict method for sparse discriminant analysis | predict.ASDA |
| Predict method for ordinal sparse discriminant analysis | predict.ordASDA |
| Print method for ASDA object | print.ASDA |
| Sparse Zero Variance Discriminant Analysis | SZVD SZVD.default |
| Cross-validation of sparse zero variance discriminant analysis | SZVD_kFold_cv SZVD_kFold_cv.default |
| Cross-validation of sparse zero variance discriminant analysis | SZVDcv SZVDcv.default |
| Zero Variance Discriminant Analysis | ZVD ZVD.default |
