location:Home > 2023 Vol.6 Jun. N0.3 > Feature Data Dimensionality Reduction Algorithm for Online English Teaching Quality Evaluation Based on Self-organizing Feature

2023 Vol.6 Jun. N0.3

  • Title: Feature Data Dimensionality Reduction Algorithm for Online English Teaching Quality Evaluation Based on Self-organizing Feature
  • Name: Sarah Aaron
  • Company: Trinity Southern University,USA
  • Abstract:

     Online English teaching is affected by many factors, and the dimension of teaching quality evaluation index is large, which leads to low fault tolerance rate of index selection, low accuracy and high uncertainty of online English teaching quality evaluation. This paper proposes a dimensionality reduction algorithm of online English teaching quality evaluation feature data based on self-organizing feature map neural network. This Paper analyzes the multi-dimensional characteristics of online English teaching quality evaluation index, constructs the online English teaching quality evaluation index system, uses the principal component analysis method to extract the multi-dimensional characteristics of online English teaching evaluation index, and introduces the Self-Organizing Feature Mapping neural network. SOFM), takes the evaluation index feature data as the input, finds out the rules and relations from the input information, calculates the proportion values corresponding to the information content of different online English teaching quality evaluation features, filters out the interference feature data with poor correlation in online English teaching quality evaluation, and achieves the purpose of dimensionality reduction of English teaching quality assessment feature data. The result of dimension reduction of the evaluation feature data is used as the output to construct the online English teaching quality evaluation method to realize the teaching quality evaluation. The experimental results show that the average fault-tolerant rate of online English teaching quality evaluation feature data is 0. 97, the accuracy of teaching quality evaluation is above 0. 97, and the evaluation uncertainty is below 0. 010, which has higher application value.


  • Keyword: Online English teaching; Teaching quality; Quality assessment; SOFM neural network; Principal component analysis;
  • DOI: 10.12250/jpciams2023090502
  • Citation form: Sarah Aaron.Feature Data Dimensionality Reduction Algorithm for Online English Teaching Quality Evaluation Based on Self-organizing Feature Map Neural Network [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.10-18
Reference:

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Tsuruta Institute of Medical Information Technology
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