文件名称：论文研究-基于簇间距离自适应的软子空间聚类算法.pdf
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更新时间：2022-09-30 11:42:38
论文研究
For the uncertain problem that intercluster distance（intercluster separation） influences on clustering in the soft subspace clustering process, a self-adaptive soft subspace clustering algorithm has been proposed based on the compactness of intracluster compactness and the intercluster distance. Minimize the intracluster compactness, and meanwhile maximize the intercluster distance based on the framework of classical k-means clustering algorithm. And a new way of computing clusters’ centers and features weighting is gotten by derivation. This way overcomes the sensitive defect of input parameters, realizes the self-adaptive learning, and obtains better clustering results.