@Article{id:Ptas2026Art,
AUTHOR = {Ptas, Wojciech and Siminski, Krzysztof},
TITLE = {The Art of Saying ‘I Don’t Know’: Learned Deferment in Neuro-Fuzzy Three-Way Decision Cascade Classifiers},
JOURNAL = {Axioms},
VOLUME = {15},
YEAR = {2026},
NUMBER = {5},
ARTICLE-NUMBER = {368},
URL = {https://www.mdpi.com/2075-1680/15/5/368},
ISSN = {2075-1680},
ABSTRACT = {The three-way decision paradigm is a new and auspicious paradigm approach to classification. 
It introduces a non-commitment region, allowing classifiers to abstain from (defer) uncertain predictions. 
This is a key mechanism in cascade classification systems, where samples assigned to the non-commitment 
region in one classifier are passed to the next one. Fixed thresholds are often used to determine 
the non-commitment region, but they require fine-tuning and provide limited insight into the reasons 
for deferment. We propose an automatic mechanism for determining the non-commitment region using auxiliary 
metaclassifiers. We reframe deferment as a learnable decision problem rather than a thresholding problem. 
Each metaclassifier predicts whether its accompanying classifier is likely to make a correct prediction 
for a given sample and decides whether to return a final answer or defer the decision to the next 
cascade stage. In this approach, deferment is based on a broader context than a single confidence threshold, 
and it is tailored to the characteristics of each classifier and dataset. With neuro-fuzzy systems used 
as metaclassifiers, deferment decisions can be expressed as human-readable rules.},
DOI = {10.3390/axioms15050368}
}