A multi-model-based deep learning framework for short text multiclass classification with the imbalanced and extremely small data set. (arXiv:2206.12027v1 [cs.CL])

Text classification plays an important role in many practical applications.
In the real world, there are extremely small datasets. Most existing methods
adopt pre-trained neural network models to handle this kind of dataset.
However, these methods are either difficult to deploy on mobile devices because
of their large output size or cannot fully extract the deep semantic
information between phrases and clauses. This paper proposes a multimodel-based
deep learning framework for short-text multiclass classification with an
imbalanced and extremely small …

arxiv classification data data set deep learning deep learning framework framework learning set small small data text