From Transformers to Voting Ensembles for Interpretable Sentiment Classification: A Comprehensive Comparison

From Transformers to Voting Ensembles for Interpretable Sentiment Classification: A Comprehensive Comparison

This study conducts an in-depth investigation of the performance of six transformer models using 12 different datasets—10 with three classes and two with two classes—on sentiment classification. We use these six models and generate all combinations of triple schema ensembles, Majority and Soft vote....

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Bibliographic Details
Main Authors: Konstantinos Kyritsis, Charalampos M. Liapis, Isidoros Perikos, Michael Paraskevas, Vaggelis Kapoulas
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Computers
Subjects:
transformer models
ensembles
classifiers
sentiment classification
machine learning
Online Access:https://www.mdpi.com/2073-431X/14/5/167
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