Xiong Xu1, Chun Zhou2,*, Chenggang Wang1, Xiaoyan Zhang2, Hua Meng2
Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 815-831, 2023, DOI:10.32604/iasc.2023.034656
- 29 April 2023
Abstract Clustering analysis is one of the main concerns in data mining. A common approach to the clustering process is to bring together points that are close to each other and separate points that are away from each other. Therefore, measuring the distance between sample points is crucial to the effectiveness of clustering. Filtering features by label information and measuring the distance between samples by these features is a common supervised learning method to reconstruct distance metric. However, in many application scenarios, it is very expensive to obtain a large number of labeled samples. In this… More >