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<p>This paper classifies the data of the original data set by random forest algorithm, selects the nodes in the attribute space for iteration, and gets the number of decision trees in the random forest. Based on the decision tree, the information gain rate in the sample set of student achievement is calculated, the spatial distance matrix of the sample set is defined, and the centroids of each cluster of the matrix indicators are separated to get the evaluation results of indicators in the student achievement evaluation reform as superior. The indicator weights of student learning achievement are evaluated through five assessment indexes, in which the teacher rating weight is the highest 10. It shows that active use of the Internet is conducive to cultivating and delivering excellent film and television production professionals to society.</p>
</abstract>

This paper classifies the data of the original data set by random forest algorithm, selects the nodes in the attribute space for iteration, and gets the number of decision trees in the random forest. Based on the decision tree, the information gain rate in the sample set of student achievement is calculated, the spatial distance matrix of the sample set is defined, and the centroids of each cluster of the matrix indicators are separated to get the evaluation results of indicators in the student achievement evaluation reform as superior. The indicator weights of student learning achievement are evaluated through five assessment indexes, in which the teacher rating weight is the highest 10. It shows that active use of the Internet is conducive to cultivating and delivering excellent film and television production professionals to society.

Research on the Reform of Film and Television Production Courses and Their Student Achievement Evaluation in Colleges and Universities in Shanxi Province Based on Random Forest Algorithm

Faculty of Social Sciences and Liberal Arts UCSI University. No.1, Jalan Menara Gading

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper classifies the data of the original data set by random forest algorithm, selects the nodes in the attribute space for iteration, and gets the number...

Research on the Reform of Film and Television Production Courses and Their Student Achievement Evaluation in Colleges and Universities in Shanxi Province Based on Random Forest Algorithm

Pubblicato online: 21 ott 2023

Pagine: -

Ricevuto: 27 dic 2022

Accettato: 01 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.00713

Parole chiave
Random forest algorithm, Decision tree, Sample set, Performance evaluation, Information gain rate

© 2023 Tianyu Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Reform of Film and Television Production Courses and Their Student Achievement Evaluation in Colleges and Universities in Shanxi Province Based on Random Forest Algorithm

Pubblicato online: 21 ott 2023

Pagine: -

Ricevuto: 27 dic 2022

Accettato: 01 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.00713

Parole chiaveRandom forest algorithm, Decision tree, Sample set, Performance evaluation, Information gain rate

© 2023 Tianyu Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Random forest algorithm, Decision tree, Sample set, Performance evaluation, Information gain rate