Text Classification
The task of assigning predefined categories or labels to text documents.
Overview
Text classification is a fundamental NLP task where a model assigns one or more predefined labels to a piece of text. Common applications include sentiment analysis, spam detection, topic categorization, intent recognition, and content moderation.
Key Details
Modern approaches use fine-tuned transformer models or leverage large language models with few-shot prompting for classification. Traditional methods include Naive Bayes, SVMs with TF-IDF features, and logistic regression. The choice of approach depends on the amount of labeled data available and latency requirements.