Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method
Abstract The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discrete points. Therefore, in order to obtain more accurate clustering results when st...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-12-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-022-00948-2 |
| _version_ | 1811177906689277952 |
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| author | Xu Gao Xiaoming Ding Tingting Han Yueyuan Kang |
| author_facet | Xu Gao Xiaoming Ding Tingting Han Yueyuan Kang |
| author_sort | Xu Gao |
| collection | DOAJ |
| description | Abstract The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discrete points. Therefore, in order to obtain more accurate clustering results when studying the factors affecting the professional growth of outstanding teachers, this paper proposes an improved algorithm of Kmeans combined with DBSCAN. Observing the clustering results of the influencing factors and calculating the evaluation standard values of the clustering results, it is found that the optimized DB-Kmeans algorithm has obvious improvements in the accuracy of the clustering results, and the clustering effect of the algorithm on edge points is more advantageous than the original algorithms according to the scatter diagram. |
| first_indexed | 2024-04-11T06:09:09Z |
| format | Article |
| id | doaj.art-e78a736294f046de950b352372535984 |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-04-11T06:09:09Z |
| publishDate | 2022-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-e78a736294f046de950b3523725359842022-12-22T04:41:22ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802022-12-012022111110.1186/s13634-022-00948-2Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans methodXu Gao0Xiaoming Ding1Tingting Han2Yueyuan Kang3College of Artificial Intelligence, Tianjin Normal UniversityCollege of Artificial Intelligence, Tianjin Normal UniversityCollege of Artificial Intelligence, Tianjin Normal UniversityFaculty of Education, Tianjin Normal UniversityAbstract The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discrete points. Therefore, in order to obtain more accurate clustering results when studying the factors affecting the professional growth of outstanding teachers, this paper proposes an improved algorithm of Kmeans combined with DBSCAN. Observing the clustering results of the influencing factors and calculating the evaluation standard values of the clustering results, it is found that the optimized DB-Kmeans algorithm has obvious improvements in the accuracy of the clustering results, and the clustering effect of the algorithm on edge points is more advantageous than the original algorithms according to the scatter diagram.https://doi.org/10.1186/s13634-022-00948-2ClusteringKmeansDBSCANEducationTeachers' professional growth |
| spellingShingle | Xu Gao Xiaoming Ding Tingting Han Yueyuan Kang Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method EURASIP Journal on Advances in Signal Processing Clustering Kmeans DBSCAN Education Teachers' professional growth |
| title | Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method |
| title_full | Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method |
| title_fullStr | Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method |
| title_full_unstemmed | Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method |
| title_short | Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method |
| title_sort | analysis of influencing factors on excellent teachers professional growth based on db kmeans method |
| topic | Clustering Kmeans DBSCAN Education Teachers' professional growth |
| url | https://doi.org/10.1186/s13634-022-00948-2 |
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