Evaluation and analysis of classroom teaching quality of art design specialty based on DBT-SVM Online publication date: Wed, 04-Oct-2023
by Junmei Guo
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 28, No. 2/3/4, 2023
Abstract: Evaluating the quality of classroom teaching in higher education can improve teachers' teaching, but the evaluating results are currently inaccurate. The study combines the binary tree support vector machine (BT-SVM) and the Euclidean distance method to obtain the distance binary tree support vector machine (DBT-SVM) algorithm. The performance of DBT-SVM algorithm is tested and compared with one versus one (OVO) algorithm and one versus rest (OVR) algorithm. The results show that the accuracy of the DBT-SVM is 92.2% and the test time is 0.02 s; it is superior to the traditional algorithms. In the empirical analysis of the evaluation model, the accuracy rate of the DBT-SVM algorithm model is 97.85%, which is superior to TW-SVM and traditional algorithm models. The results show that the performance of the optimised DBT-SVM algorithm has greatly improved the accuracy and test time of the traditional SVM algorithm.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook