Other packages > Find by keyword >

HNPclassifier  

Hierarchical Neyman-Pearson Classification for Ordered Classes
View on CRAN: Click here


Download and install HNPclassifier package within the R console
Install from CRAN:
install.packages("HNPclassifier")

Install from Github:
library("remotes")
install_github("cran/HNPclassifier")

Install by package version:
library("remotes")
install_version("HNPclassifier", "0.1.0")



Attach the package and use:
library("HNPclassifier")
Maintained by
Che Shen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-08
Latest Update: 2026-02-08
Description:
The Hierarchical Neyman-Pearson (H-NP) classification framework extends the Neyman-Pearson classification paradigm to multi-class settings where classes have a natural priority ordering. This is particularly useful for classification in unbalanced dataset, for example, disease severity classification, where under-classification errors (misclassifying patients into less severe categories) are more consequential than other misclassifications. The package implements H-NP umbrella algorithms that controls under-classification errors under user specified control levels with high probability. It supports the creation of H-NP classifiers using scoring functions based on built-in classification methods (including logistic regression, support vector machines, and random forests), as well as user-trained scoring functions. For theoretical details, please refer to Lijia Wang, Y. X. Rachel Wang, Jingyi Jessica Li & Xin Tong (2024) <doi:10.1080/01621459.2023.2270657>.
How to cite:
Che Shen (2026). HNPclassifier: Hierarchical Neyman-Pearson Classification for Ordered Classes. R package version 0.1.0, https://cran.r-project.org/web/packages/HNPclassifier. Accessed 07 Aug. 2026.
Previous versions and publish date:
0.1.0 (2026-02-08 17:40), 0.2.0 (2026-06-27 08:40), (2026-07-14 09:00)
Other packages that cited HNPclassifier R package
View HNPclassifier citation profile
Other R packages that HNPclassifier depends, imports, suggests or enhances
Complete documentation for HNPclassifier
Functions, R codes and Examples using the HNPclassifier R package
Full HNPclassifier package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

BayesESS  
Determining Effective Sample Size
Determines effective sample size of a parametric prior distribution in Bayesian models. For a web-b ...
Download / Learn more Package Citations See dependency  
bbricks  
Bayesian Methods and Graphical Model Structures for Statistical Modeling
A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
enrichwith  
Methods to Enrich R Objects with Extra Components
Provides the "enrich" method to enrich list-like R objects with new, relevant components. The curren ...
Download / Learn more Package Citations See dependency  
modelwordcloud  
Model Word Clouds
Makes a word cloud of text, sized by the frequency of the word, and colored either by user-specified ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA