Volume 43 Issue 1
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JOURNAL OF MECHANICAL ENGINEERING  > 2017  >  43(1): 28-35.
JIA Xibin, LI Ning, JIN Ya. Dynamic Convolutional Neural Network Extreme Learning Machine for Text Sentiment Classification[J]. JOURNAL OF MECHANICAL ENGINEERING, 2017, 43(1): 28-35. doi: 10.11936/bjutxb2016040093
Citation: JIA Xibin, LI Ning, JIN Ya. Dynamic Convolutional Neural Network Extreme Learning Machine for Text Sentiment Classification[J]. JOURNAL OF MECHANICAL ENGINEERING, 2017, 43(1): 28-35. doi: 10.11936/bjutxb2016040093
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Dynamic Convolutional Neural Network Extreme Learning Machine for Text Sentiment Classification

doi: 10.11936/bjutxb2016040093

  • College of Computer Science, Beijing University of Technology, Beijing 100124, China

  • Received Date: 27 Apr 2016
    Available Online: 09 Sep 2022
  • Issue Publish Date: 01 Jan 2017
    Abstract
  • Aim ing at improving the generalization performance of the dynamic convolutional neural network on text sentiment classification, a dynamic convolutional extreme learning machine algorithm was proposed. This algorithm modified the output layer of dynamic convolutional neural network by replacing the fully connection layer with the shallow random neural network. By utilizing the perturbation ability of the random generation of parameters, it is prone to mitigate the dependence on training samples and avoid over-fitting to improve the classification performance. Experiments on several public data sets show that this approach outperforms the dynamic convolutional neural network and extreme learning machine under the evaluation metrics including accuracy rate, F1-measure, etc.

     

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