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:Dincer Goksuluk [aut, cre], Gokmen Zararsiz [aut], Selcuk Korkmaz [aut], Ahmet Ergun Karaagaoglu [ths]

NBLDA_1.0.1.9000.tar.gz
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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'))

Peer review:

Bug tracker:https://github.com/dncr/nblda/issues

Datasets:

On CRAN:

3.54 score 2 scripts 686 downloads 7 mentions 15 exports 28 dependencies

Last updated 3 years agofrom:3b098934a8. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winOKNov 05 2024
R-4.5-linuxOKNov 05 2024
R-4.4-winOKNov 05 2024
R-4.4-macOKNov 05 2024
R-4.3-winOKNov 05 2024
R-4.3-macOKNov 05 2024

Exports:controlFindBestTransformgenerateCountDatagetShrinkedDispersionsinputsnbldaControlnbldaTrainednormalizationNullModelNullModelTestplotpredictselectedFeaturesshowtrainNBLDA

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Classifying count data using Poisson/Negative Binomial linear discriminant analysisNBLDA-package
Cervical cancer datacervical
Accessors for the 'control' slot.control control,nblda-method control,nblda_trained-method
Find the Power Transformation Parameter.FindBestTransform
Generate Count DatagenerateCountData
Estimate Shrinked OverdispersionsgetShrinkedDispersions
Accessors for the 'input' slot.inputs inputs,nblda-method
'nblda_input' objectnblda_input-class
'nblda_trained' objectnblda_trained-class
'nblda' objectnblda-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' Classesplot plot,nblda-method plot,nblda_trained-method plot.nblda plot.nblda_trained
Extract predictions from NBLDA modelpredict 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 Packageshow show,nblda-method show,nblda_input-method show,nblda_trained-method show.nblda show.nblda_input show.nblda_trained
Train Model over Different Tuning ParameterstrainNBLDA