Jili Chen1,2, Hailan Wang2, Xiaolan Xie1,2,*
Computer Systems Science and Engineering, Vol.48, No.3, pp. 645-663, 2024, DOI:10.32604/csse.2023.037957
- 20 May 2024
Abstract Fuzzy C-Means (FCM) is an effective and widely used clustering algorithm, but there are still some problems. considering the number of clusters must be determined manually, the local optimal solutions is easily influenced by the random selection of initial cluster centers, and the performance of Euclid distance in complex high-dimensional data is poor. To solve the above problems, the improved FCM clustering algorithm based on density Canopy and Manifold learning (DM-FCM) is proposed. First, a density Canopy algorithm based on improved local density is proposed to automatically deter-mine the number of clusters and initial cluster… More >
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