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- W4387385181 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." @default.
- W4387385181 created "2023-10-06" @default.
- W4387385181 creator A5041398286 @default.
- W4387385181 date "2023-01-01" @default.
- W4387385181 modified "2023-10-16" @default.
- W4387385181 title "Evaluation and analysis of classroom teaching quality of art design specialty based on DBT-SVM" @default.
- W4387385181 doi "https://doi.org/10.1504/ijnvo.2023.133833" @default.
- W4387385181 hasPublicationYear "2023" @default.
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