<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>Integrating the ideological science embedded in curriculum thinking into the development of grassroots party building to activate the nurturing function of curriculum thinking. In this paper, the principle of the XGBoost algorithm is explained from the Internet+ perspective, and the Taylor expansion is performed using the regularization term and the objective function to optimize the objective function of the XGBoost algorithm. Then the XGBoost model is trained to determine its optimal splitting nodes, and the model’s performance is evaluated by the ten-fold cross-validation method. The XGBoost model was then used to analyze the development data of a university’s curriculum thinking and politics integrated into grassroots party building and to explore its nurturing function and nurturing mode. From the performance evaluation, the average accuracy, precision, and recall were 88.59%, 83.46%, and 84.54%, respectively, and the average comprehensive evaluation index was 0.845, and all the indexes met the expected performance requirements of the model. From the perspective of the nurturing model, the mean values of whole-person nurturing, whole-process nurturing, and all-round nurturing are 36.77%, 23.03%, and 40.19%, respectively, and the curriculum thinking and government can be perfectly integrated into the grassroots party building and fully enhance its nurturing function. Under the Internet+ perspective, the XGBoost model is used to analyze the corresponding data on the integration of curriculum thinking politics into grassroots party building, which can provide new directions for developing grassroots party building and curriculum thinking politics.</p>
</abstract>

Integrating the ideological science embedded in curriculum thinking into the development of grassroots party building to activate the nurturing function of curriculum thinking. In this paper, the principle of the XGBoost algorithm is explained from the Internet+ perspective, and the Taylor expansion is performed using the regularization term and the objective function to optimize the objective function of the XGBoost algorithm. Then the XGBoost model is trained to determine its optimal splitting nodes, and the model’s performance is evaluated by the ten-fold cross-validation method. The XGBoost model was then used to analyze the development data of a university’s curriculum thinking and politics integrated into grassroots party building and to explore its nurturing function and nurturing mode. From the performance evaluation, the average accuracy, precision, and recall were 88.59%, 83.46%, and 84.54%, respectively, and the average comprehensive evaluation index was 0.845, and all the indexes met the expected performance requirements of the model. From the perspective of the nurturing model, the mean values of whole-person nurturing, whole-process nurturing, and all-round nurturing are 36.77%, 23.03%, and 40.19%, respectively, and the curriculum thinking and government can be perfectly integrated into the grassroots party building and fully enhance its nurturing function. Under the Internet+ perspective, the XGBoost model is used to analyze the corresponding data on the integration of curriculum thinking politics into grassroots party building, which can provide new directions for developing grassroots party building and curriculum thinking politics.

Research on the integration of curriculum thinking and politics into the construction of grassroots party building and nurturing work under the perspective of Internet+

Applied Mathematics and Nonlinear Sciences

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

Integrating the ideological science embedded in curriculum thinking into the development of grassroots party building to activate the nurturing function of...

Research on the integration of curriculum thinking and politics into the construction of grassroots party building and nurturing work under the perspective of Internet+

Online veröffentlicht: 01. Aug. 2023

Seitenbereich: -

Eingereicht: 11. Sept. 2022

Akzeptiert: 09. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00121

Schlüsselwörter
Internet+ vision, XGBoost model, Objective function, Parenting model

© 2023 Jinyan Huang, published by Sciendo

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

Research on the integration of curriculum thinking and politics into the construction of grassroots party building and nurturing work under the perspective of Internet+

Online veröffentlicht: 01. Aug. 2023

Seitenbereich: -

Eingereicht: 11. Sept. 2022

Akzeptiert: 09. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00121

SchlüsselwörterInternet+ vision, XGBoost model, Objective function, Parenting model

© 2023 Jinyan Huang, published by Sciendo

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

Schlüsselwörter
Internet+ vision, XGBoost model, Objective function, Parenting model