Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm


Fang Dou, Journal of Information Processing Systems Vol. 18, No. 4, pp. 500-509, Aug. 2022  

10.3745/JIPS.04.0248
Keywords: Association Rules, Characteristic Interval Value, English Education, Improved Decision Tree, Incremental Algorithm
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Abstract

With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers’ professional skills in an accelerated manner and perfect the education system.


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Cite this article
[APA Style]
Fang Dou (2022). Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm. Journal of Information Processing Systems, 18(4), 500-509. DOI: 10.3745/JIPS.04.0248.

[IEEE Style]
F. Dou, "Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm," Journal of Information Processing Systems, vol. 18, no. 4, pp. 500-509, 2022. DOI: 10.3745/JIPS.04.0248.

[ACM Style]
Fang Dou. 2022. Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm. Journal of Information Processing Systems, 18, 4, (2022), 500-509. DOI: 10.3745/JIPS.04.0248.