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引用次数: 0

摘要

介绍了拓扑结构和规则拓扑结构,目的是寻求具有规则拓扑结构的低维数据集的结构拓扑结构的规律性,并提出了保持数据集拓扑结构局部规则嵌入的方法。与局部线性嵌入、拉普拉斯特征映射等核特征映射方法相比,低维嵌入结果近似规则,数据分类更具有自然联系。最后的结果证明了理论结果表明,与LLE和拉普拉斯特征映射相比,该技术可以很好地发现数据的拓扑结构。
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Notice of Retraction Locally regular embedding
Introducing the topological structure and regular topology structure, the purpose is to seek with regular topological structure of low dimensional data set, the structural topological structure regularity, and puts forward the measure to keep data set topology structure of local rules embedding method. Compared to nuclear feature mapping methods, such as Locally Linear Embedding, Laplacian Eigenmap and so on, low dimensional embedded result is approximately regular, and data classification has more natural connection. The last results prove the theory results show that this technique can greatly discover the topological structure of data, compared to the LLE and Laplacian Eigenmap.
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