Towards a polynomial approximation of support vector machine accuracy applied to Arabic tweet sentiment analysis
Zouheir Banou, S. Elfilali, El Habib Benlahmar · Mathematical Modeling and Computing · 2023
Machine learning algorithms have become very frequently used in natural language processing, notably sentiment analysis, which helps determine the general feeling carried within a text. Among these algorithms, Support Vector Machines have proven powerful classifiers especially in such a task, when their performance is assessed through accuracy score and f1-score. However, they remain slow in terms of training, thus making exhaustive grid-search experimentations very time-consuming. In this paper, we present an observed pattern in SVM's accuracy, and f1-score approximated with a Lagrange polynomial.