Rank-Constrained Spectral Clustering With Flexible Embedding.

Zhihui Li,Feiping Nie,Xiaojun Chang,Liqiang Nie,Huaxiang Zhang,Yi Yang

IEEE Transactions on Neural Networks and Learning Systems（2018）

引用 204|浏览106

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摘要

Spectral clustering (SC) has been proven to be effective in various applications. However, the learning scheme of SC is suboptimal in that it learns the cluster indicator from a fixed graph structure, which usually requires a rounding procedure to further partition the data. Also, the obtained cluster number cannot reflect the ground truth number of connected components in the graph. To alleviate ...

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关键词

Clustering algorithms,Laplace equations,Dimensionality reduction,Manifolds,Learning systems

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