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tbnb

0.1.0

Threshold-Based and Iterative Threshold-Based Naive Bayes Classifier

0packages depend
261downloads / year
79.1%test coverage
13/13checks pass

Overview

About
Maintained by Maurizio RomanoFirst published 2026-07-211 releasesCRAN page ↗

Implements the Threshold-Based Naive Bayes (Tb-NB) classifier and its iterative refinement (iTb-NB) for binary sentiment / text classification problems. The classifier computes a continuous log-likelihood ratio score per document and uses a data-driven decision threshold estimated via K-fold cross-validation on a user-selected criterion (accuracy, F1 score, Matthews correlation coefficient, balanced error, etc.). An optional iterative refinement procedure locally re-estimates the threshold in regions of class overlap using either Gaussian kernel density estimation or a Central Limit Theorem bootstrap approximation. The package exposes an idiomatic R formula + data.frame interface together with a 'quanteda'-based text preprocessing pipeline, supports user-supplied document-feature matrices, and includes an optional word-embedding extension that augments the Bag-of-Words with K nearest semantic neighbours of each token. The package additionally implements the p-value extension proposed by Romano (2025) for both document- and feature-level interpretability via tbnb_pvalues(). Methods are described in Romano, Contu, Mola, Conversano (2024) doi:10.1007/s11634-023-00536-8, Romano, Zammarchi, Conversano (2024) doi:10.1007/s10260-023-00721-1, and Romano (2025) doi:10.1007/978-3-031-96736-8_41.

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.27
79.1%
Coverage · measured lines
100%
Documentation · exports
6
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-07-22
    7 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 369 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
0%
Documented parameters
72%
Return-value docs
100%
References docs
29%

Downloads

261
CRAN downloads in the past year
Rank #24,384 · ~1/day · ~22/mo
Daily download trend is not available in this view yet.
23030 days
26190 days
2611 year
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Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.0
Imports (6)
MatrixmethodsstatsgrDevicesgraphicsquanteda (>= 3.0.0)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • 0.1.0Latest
    2026-07-21 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-07-21
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0
Bundled data
3.1 KB / 1 file
Download size
253 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("tbnb")
Romano, M. (2026). tbnb: Threshold-Based and Iterative Threshold-Based Naive Bayes Classifier (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.tbnb

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for tbnb version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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