Text Classification Model

Text classification models automatically categorize text into predefined classes, aiming to improve efficiency and accuracy in tasks ranging from spam detection to sentiment analysis. Current research emphasizes addressing challenges like data imbalance through synthetic data generation and visual analytics, enhancing model robustness against adversarial attacks and mitigating privacy concerns via token manipulation techniques. These advancements are crucial for improving the reliability and ethical deployment of text classification in diverse applications, including e-commerce, healthcare, and social media monitoring.