tbnb: Threshold-Based and Iterative Threshold-Based Naive Bayes
Classifier
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>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.0) |
| Imports: |
Matrix, methods, stats, grDevices, graphics, quanteda (≥
3.0.0) |
| Suggests: |
text2vec, stopwords, SnowballC, cld2, cld3, dbscan, viridisLite, testthat (≥ 3.0.0), ggplot2 |
| Published: |
2026-07-21 |
| DOI: |
10.32614/CRAN.package.tbnb (may not be active yet) |
| Author: |
Maurizio Romano [aut, cre] |
| Maintainer: |
Maurizio Romano <romano.maurizio at unica.it> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| Language: |
en-GB |
| Materials: |
README, NEWS |
| CRAN checks: |
tbnb results |
Documentation:
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