What is ensemble learning in natural language processing (NLP)?

NLP ensembles combine multiple language models or feature representations to improve text understanding.

In NLP, ensembles combine TF-IDF models, transformer-based models, and sequence models. Each captures different aspects: TF-IDF captures lexical signals, transformers capture contextual meaning, and sequence models capture order dependencies. Ensemble methods improve performance in classification, translation, and sentiment analysis tasks by reducing model bias and variance.