CVAP: Validation for Cluster Analyses
Evaluation of clustering results (or cluster validation) is an important and necessary step in cluster analysis, but it is often time-consuming and complicated work. We present a visual cluster validation tool, the Cluster Validity Analysis Platform (CVAP), to facilitate cluster validation. The CVAP...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ubiquity Press
2009-04-01
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| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | http://datascience.codata.org/articles/222 |
| _version_ | 1817993764086480896 |
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| author | Kaijun Wang Baijie Wang Liuqing Peng |
| author_facet | Kaijun Wang Baijie Wang Liuqing Peng |
| author_sort | Kaijun Wang |
| collection | DOAJ |
| description | Evaluation of clustering results (or cluster validation) is an important and necessary step in cluster analysis, but it is often time-consuming and complicated work. We present a visual cluster validation tool, the Cluster Validity Analysis Platform (CVAP), to facilitate cluster validation. The CVAP provides necessary methods (e.g., many validity indices, several clustering algorithms and procedures) and an analysis environment for clustering, evaluation of clustering results, estimation of the number of clusters, and performance comparison among different clustering algorithms. It can help users accomplish their clustering tasks faster and easier and help achieve good clustering quality when there is little prior knowledge about the cluster structure of a data set. |
| first_indexed | 2024-04-14T01:44:08Z |
| format | Article |
| id | doaj.art-8a00a33a4a984362885ae4dc0965ee1f |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-04-14T01:44:08Z |
| publishDate | 2009-04-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-8a00a33a4a984362885ae4dc0965ee1f2022-12-22T02:19:37ZengUbiquity PressData Science Journal1683-14702009-04-018889310.2481/dsj.007-020222CVAP: Validation for Cluster AnalysesKaijun Wang0Baijie Wang1Liuqing Peng2School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, P. R. ChinaSchool of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.School of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.Evaluation of clustering results (or cluster validation) is an important and necessary step in cluster analysis, but it is often time-consuming and complicated work. We present a visual cluster validation tool, the Cluster Validity Analysis Platform (CVAP), to facilitate cluster validation. The CVAP provides necessary methods (e.g., many validity indices, several clustering algorithms and procedures) and an analysis environment for clustering, evaluation of clustering results, estimation of the number of clusters, and performance comparison among different clustering algorithms. It can help users accomplish their clustering tasks faster and easier and help achieve good clustering quality when there is little prior knowledge about the cluster structure of a data set.http://datascience.codata.org/articles/222Cluster validationValidity indicesVisual cluster analysis environment |
| spellingShingle | Kaijun Wang Baijie Wang Liuqing Peng CVAP: Validation for Cluster Analyses Data Science Journal Cluster validation Validity indices Visual cluster analysis environment |
| title | CVAP: Validation for Cluster Analyses |
| title_full | CVAP: Validation for Cluster Analyses |
| title_fullStr | CVAP: Validation for Cluster Analyses |
| title_full_unstemmed | CVAP: Validation for Cluster Analyses |
| title_short | CVAP: Validation for Cluster Analyses |
| title_sort | cvap validation for cluster analyses |
| topic | Cluster validation Validity indices Visual cluster analysis environment |
| url | http://datascience.codata.org/articles/222 |
| work_keys_str_mv | AT kaijunwang cvapvalidationforclusteranalyses AT baijiewang cvapvalidationforclusteranalyses AT liuqingpeng cvapvalidationforclusteranalyses |