# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "tbnb" in publications use:' type: software license: GPL-3.0-or-later title: 'tbnb: Threshold-Based and Iterative Threshold-Based Naive Bayes Classifier' version: 0.1.0 abstract: 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) , Romano, Zammarchi, Conversano (2024) , and Romano (2025) . authors: - family-names: Romano given-names: Maurizio email: romano.maurizio@unica.it repository: https://cran.r-universe.dev commit: faa86269cf5f9a5b901b1d2fe9a0fab1d641af93 date-released: '2026-07-21' contact: - family-names: Romano given-names: Maurizio email: romano.maurizio@unica.it