… used text classification techniques, and 2) through that understanding, to improve upon
the tools that are available for text classification. Naive Bayes is the de-facto standard text …

… BERT based models for binary text classification tasks. Our work is very closely related to
this work with the difference that we focus on experiments with multi-class text classification. …

… the task of multi-class text classification for the texts written in Uzbek. … multi-class, multi-label
problems [17]. In our work, we discuss the task of multi-class text classification for the texts …

… In this study, we investigate the case of multi-class text classification, a task that is relatively
less studied in the literature evaluating pre-trained language models. Our work is further …

… In Section 4 we evaluate the performance improvement on a set of 19 multi-class text
classification tasks. We summarize and suggest future work in Section 5. The balance of the …

… categories of documents correctly when the texts are in cross zones of … In this paper, we
propose an approach named as Multi-class … the performance of multi-class text classification. The …

… Text search and classification tools … on multi-class topic classification of text fragments
containing biographical information using supervised learning methods. We use sentences as text …

… Our work centers on the comparison of these classification algorithms and the response …
multi-class text classification?” We have done a thorough comparison among text classification …

… Naïve Bayesian classifier applied on multi-class text datasets: Multi-class Odds Ratio (MOR)…
of text classification with Naïve Bayesian classifiers were carried out on two multi-class texts …

… on multi-class text classification, it is clear that the performance of different text classification
… Apart from this, the performance of these multi-class text classification models is also …