Document classification, a critical area of research, employs machine and deep learning
methods to solve real-world problems. This study attempts to highlight the qualitative and …

Feature selection is a crucial technique in text classification for improving the efficiency and
effectiveness of classifiers or machine learning techniques by reducing the dataset's …

The increasing proliferation of electronic files in recent decades has been addressed by
significant improvements in Natural Language Processing. As the text data generated is …

Obesity is a global crisis leading to several metabolic disorders. Modernization and
technology innovation has been easier for next generation sequencing using open-source …

Recently, transformer models have gained interest with their varied range of natural
language applications in several domains like education, healthcare, entertainment, and the …

Technology and social media's growing prevalence, especially during the COVID-19
pandemic, has contributed to a rise in mental health issues. This research discusses novel …

Supervised learning methods demand large scores of labelled training data to achieve high
predictive accuracy for classification problems. In contrast, the less accurate unsupervised …

Previous works have proposed various techniques to address the premature convergence
problem, where candidate solutions get trapped in local optima instead of reaching the …