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arXiv · 2010.14784

A Chinese Text Classification Method With Low Hardware Requirement Based on Improved Model Concatenation

Qingli Man·Yuanhao Zhuo
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Abstract

In order to improve the accuracy performance of Chinese text classification models with low hardware requirements, an improved concatenation-based model is designed in this paper, which is a concatenation of 5 different sub-models, including TextCNN, LSTM, and Bi-LSTM. Compared with the existing ensemble learning method, for a text classification mission, this model's accuracy is 2% higher. Meanwhile, the hardware requirements of this model are much lower than the BERT-based model.

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Qingli Man, Yuanhao Zhuo. 2020-10-28. A Chinese Text Classification Method With Low Hardware Requirement Based on Improved Model Concatenation. https://arxiv.org/abs/2010.14784

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