Open AccessDimensionality Reduction and Regression Analysis Based on the Data of Educational Participation of Student Party Member
Author(s) -
Jing Li,
DengShan Wang,
Xiaojuan Xu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1437/1/012002
Subject(s) - regression analysis , index (typography) , curse of dimensionality , construct (python library) , statistics , dimension (graph theory) , class (philosophy) , psychology , dimensionality reduction , regression , value (mathematics) , mathematics , mathematics education , computer science , artificial intelligence , world wide web , pure mathematics , programming language
This study adopts the multi-stage random sampling method of grade, major and class. Data were obtained through questionnaires. Through the analysis of the questionnaire data, we find that the grade and identity distribution of the respondents are relatively uniform among the respondents. Taking the arithmetic mean value of each secondary index, we construct the dimension index based on the data of questionnaires. By least square and generalized linear regression model, we find that the influence of independent participation on the learning harvest is significantly positive, indicating that the daily party member education activities such as active participation and social practice can significantly improve the learning harvest.