Extraction and analysis of individual features of students’ ideological and political education based on big data clustering algorithm
and
Mar 19, 2025
About this article
Published Online: Mar 19, 2025
Received: Oct 27, 2024
Accepted: Feb 18, 2025
DOI: https://doi.org/10.2478/amns-2025-0531
Keywords
© 2025 Ying Zhai, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Figure 1.
Figure 2.
Figure 3.
Clustering table of TGI values of student group characteristics
| Group division label classification | Groups with learning difficulties | Groups with financial difficulties | Group with psychological difficulties | Groups with employment difficulties | General group |
|---|---|---|---|---|---|
| Diligence | 82.89 | 84.92 | 88.03 | 81.47 | 94.18 |
| Sleep pattern | 159.23 | 92.11 | 110.35 | 137.35 | 98.46 |
| Consumption behavior | 105.32 | 74.92 | 101.29 | 102.51 | 103.63 |
The Possible values table of two element type variables
| Object |
Object |
1 | 0 | sum |
|---|---|---|---|---|
| 1 | ||||
| 0 | ||||
| sum | ||||
Student consumption behavior data
| Student number | Average monthly consumption/Yuan | Average monthly consumption/Yuan | Average monthly consumption frequency/yuan |
|---|---|---|---|
| 201901**** | 739.54 | 820.24 | 73.0 |
| 201901**** | 832.28 | 1093.13 | 87.3 |
| 201901**** | 428.42 | 592.01 | 50.3 |
| 201901**** | 924.14 | 1093.23 | 59.1 |
| 201901**** | 380.09 | 532.08 | 50.2 |
| 201901**** | 879.24 | 967.29 | 78.5 |
| 201901**** | 921.33 | 987.23 | 79.2 |
| 201901**** | 350.20 | 380.92 | 48.3 |
| 201901**** | 730.29 | 829.34 | 78.1 |
| 201901**** | 926.24 | 988.26 | 80.5 |
| 201901**** | 539.21 | 678.29 | 67.9 |
| 201901**** | 370.13 | 540.23 | 73.2 |
| 201901**** | 863.92 | 930.92 | 64.1 |
| 201901**** | 572.39 | 783.93 | 70.3 |