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In this paper we proposed a fast bipartite graph spectral algorithm which uses evidence accumulation method and algebraic transformation method to avoid the ...
It is a graph-based algorithm capable of handling arbitrarily distributed data. However, the distances of all samples in the high-dimensional space tend to be ...
A spectral clustering based on hierarchical bipartite graph approach is proposed. •. The approach could solve the large scale data better.
May 23, 2022 · In order to overcome these problems, a new fast spectral clustering algorithm based on multi-layer bipartite graph is proposed. Firstly, the ...
Oct 1, 2023 · Spectral Clustering (SC) is a widespread used clustering algorithm in data mining, image processing, etc. It is a graph-based algorithm capable ...
... In this method, the similarity with respect to anchor graph is calculated between the original data and a small number of representative points [5,32,39].
Jul 18, 2022 · Firstly, a fuzzy similarity matrix is constructed by using the bipartite graph to obtain low-dimensional hyper-spectral data, which can reduce ...
Semantic Scholar extracted view of "Fast spectral clustering learning with hierarchical bipartite graph for large-scale data" by Xiaojun Yang et al.
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Fig. 2. Clustering graphs of different algorithms in Indian Pines data set. (a) Real image; (b) K-means algorithm; (c) FCM algorithm; (d) FCM_S1 algorithm; ...
Abstract. In the past decades, Spectral Clustering (SC) has become one of the most effective clustering approaches. Although it has.