Package: NBLDA 1.0.1.9000
NBLDA: Negative Binomial Linear Discriminant Analysis
We proposed a package for the classification task which uses Negative Binomial distribution within Linear Discriminant Analysis (NBLDA). It is an extension of the 'PoiClaClu' package to Negative Binomial distribution. The classification algorithms are based on the papers Dong et al. (2016, ISSN: 1471-2105) and Witten, DM (2011, ISSN: 1932-6157) for NBLDA and PLDA, respectively. Although PLDA is a sparse algorithm and can be used for variable selection, the algorithm proposed by Dong et al. is not sparse. Therefore, it uses all variables in the classifier. Here, we extend Dong et al.'s algorithm to the sparse case by shrinking overdispersion towards 0 (Yu et al., 2013, ISSN: 1367-4803) and offset parameter towards 1 (as proposed by Witten DM, 2011). We support only the classification task with this version.
Authors:
NBLDA_1.0.1.9000.tar.gz
NBLDA_1.0.1.9000.zip(r-4.5)NBLDA_1.0.1.9000.zip(r-4.4)NBLDA_1.0.1.9000.zip(r-4.3)
NBLDA_1.0.1.9000.tgz(r-4.4-any)NBLDA_1.0.1.9000.tgz(r-4.3-any)
NBLDA_1.0.1.9000.tar.gz(r-4.5-noble)NBLDA_1.0.1.9000.tar.gz(r-4.4-noble)
NBLDA_1.0.1.9000.tgz(r-4.4-emscripten)NBLDA_1.0.1.9000.tgz(r-4.3-emscripten)
NBLDA.pdf |NBLDA.html✨
NBLDA/json (API)
| # Install 'NBLDA' in R: |
| install.packages('NBLDA', repos = c('https://dncr.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dncr/nblda/issues
- cervical - Cervical cancer data
Last updated 3 years agofrom:3b098934a8. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 06 2024 |
| R-4.5-win | OK | Sep 06 2024 |
| R-4.5-linux | OK | Sep 06 2024 |
| R-4.4-win | OK | Sep 06 2024 |
| R-4.4-mac | OK | Sep 06 2024 |
| R-4.3-win | OK | Sep 06 2024 |
| R-4.3-mac | OK | Sep 06 2024 |
Exports:controlFindBestTransformgenerateCountDatagetShrinkedDispersionsinputsnbldaControlnbldaTrainednormalizationNullModelNullModelTestplotpredictselectedFeaturesshowtrainNBLDA
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Classifying count data using Poisson/Negative Binomial linear discriminant analysis | NBLDA-package |
| Cervical cancer data | cervical |
| Accessors for the 'control' slot. | control control,nblda-method control,nblda_trained-method |
| Find the Power Transformation Parameter. | FindBestTransform |
| Generate Count Data | generateCountData |
| Estimate Shrinked Overdispersions | getShrinkedDispersions |
| Accessors for the 'input' slot. | inputs inputs,nblda-method |
| 'nblda_input' object | nblda_input-class |
| 'nblda_trained' object | nblda_trained-class |
| 'nblda' object | nblda-class |
| Control parameters for trained NBLDA model. | nbldaControl |
| Accessors for the 'crossValidated' slot. | nbldaTrained nbldaTrained,nblda-method nbldaTrained,nblda_trained-method |
| Accessors for the 'type' slot. | normalization normalization,nblda-method normalization,nblda_trained-method |
| Calculate the Normalized Counts and Related Training Parameters. | NullModel NullModelTest |
| Plot Method for the 'nblda' and 'nblda_trained' Classes | plot plot,nblda-method plot,nblda_trained-method plot.nblda plot.nblda_trained |
| Extract predictions from NBLDA model | predict predict,nblda-method predict.nblda |
| Accessors for the 'selectedFeatures' slot. | selectedFeatures selectedFeatures,nblda-method selectedFeatures,nblda_trained-method |
| Show Method for the S4 classes in NBLDA Package | show show,nblda-method show,nblda_input-method show,nblda_trained-method show.nblda show.nblda_input show.nblda_trained |
| Train Model over Different Tuning Parameters | trainNBLDA |
