PDEnaiveBayes-package: Plausible Naive Bayes Classifier Using PDE

In PDEnaiveBayes: Plausible Naive Bayes Classifier Using PDE

Plausible Naive Bayes Classifier Using PDE

Description

A nonparametric, multicore-capable plausible naive Bayes classifier based on the Pareto density estimation (PDE) featuring a plausible approach to a pitfall in the Bayesian theorem covering low evidence cases. Stier, Q., Hoffmann, J., and Thrun, M.C.: "Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naïve Bayes" (2025).

Details

Pareto Density Estimated naive Bayes Classifier Index: This package was not yet installed at build time.
(PDENB)

Author(s)

Michal Thrun

Maintainer: Michael Thrun <[e-mail]>

References

[Thrun et al., 2020] Thrun, M. C., Gehlert, T., & Ultsch, A.: Analyzing the Fine Structure of Distributions, PloS one, Vol. 15(10), pp. e0238835, doi 10.1371/journal.pone.0238835 2020.

[Thrun/Ultsch, 2020] Thrun, M. C., & Ultsch, A.: Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems, Data in Brief, Vol. 30(C), pp. 105501, doi 10.1016/j.dib.2020.105501, 2020.

[Ultsch et al., 2015] Ultsch, A., Thrun, M. C., Hansen-Goos, O., & L?tsch, J.: Identification of Molecular Fingerprints in Human Heat Pain Thresholds by Use of an Interactive Mixture Model R Toolbox (AdaptGauss), International journal of molecular sciences, Vol. 16(10), pp. 25897-25911, doi 10.3390/ijms161025897, 2015.

Examples

if(requireNamespace("FCPS")){
V=FCPS::ClusterChallenge("Hepta",1000)
Data=V$Hepta
Cls=V$Cls
ind=1:length(Cls)
indtrain=sample(ind,800)
indtest=setdiff(ind,indtrain)
#parametric
#model=Train_naiveBayes(Data[indtrain,],Cls[indtrain],Gaussian=TRUE)
#ClsTrain=model$ClsTrain
#table(Cls[indtrain],ClsTrain)

#res=Predict_naiveBayes(Data[indtest,], Model = model)
#table(Cls[indtest],res$ClsTest)

#PDEbayes
model=Train_naiveBayes(Data[indtrain,],Cls[indtrain],Gaussian=FALSE)
ClsTrain=model$ClsTrain
table(Cls[indtrain],ClsTrain)

res=Predict_naiveBayes(Data[indtest,], Model = model)
table(Cls[indtest],res$ClsTest)
}

PDEnaiveBayes documentation built on Nov. 17, 2025, 5:07 p.m.