Unsupervised Text Classification with Lbl2Vec

Text classification is the task of assigning a sentence or document an appropriate category. The categories depend on the selected dataset and can cover arbitrary subjects. Therefore, text classifiers can be used to organize, structure, and categorize any kind of text. Common approaches use supervised learning to classify texts. Especially BERT-based language models achieved very good text classification results in recent years.