H.D. Men´endez, F.E.B. Otero, and D. Camacho. SACOC: A spectral-based ACO clustering algorithm. In Intelligent Distributed Computing VIII, pages 185-194. Springer, 2015.Hector D. Menendez, Fernando E. B. Oter
如[7]里面,Spectral Algorithm用来将点集分成树状,然后在树上以其它准则(如K-means) 将树叶合并回去,形成最终的聚类结果。在树上很多本来np-hard的问题就变成可以用动态规划解了。 11. Spectral Embedding 一些非线性降维的方法除了Spectral clustering, Spectral Embedding即用spectral algorithm来进行非线性降维,也是谱...
The Cheeger cut criterion is used in p-spectral clustering to do graph partition. However, due to the improper affinity measure and outliers, the original p-spectral clustering algorithm is not effective in dealing with manifold data. To solve this problem, we propose a manifold p-spectral ...
In the previous work, we showed that for sparse or low-dimensional data, spectral clustering with the cosine similarity can be implemented directly through efficient operations on the data matrix such as elementwise manipulation, matrix-vector multiplication and low-rank SVD, thus completely avoiding ...
网络谱聚类算法 网络释义 1. 谱聚类算法 谱聚类算法(spectral clustering algorithm)避免了这个问题。该算法建立在图论中的谱图理论基础上,其本质是将聚类问题转换为 … www.xueshuqikan.cn|基于13个网页 例句
Spectral Clustering算法的全貌: 1)根据数据构造一个Graph,Graph的每一个节点对应一个数据点,将相似的点连接起来,并且边的权重用于表示数据之间的相似度。把这个Graph用邻接矩阵的形式表示出来,记为W。 2)把的每一列元素加起来得到N个数,把它们放在对角线上(其他地方都是零),组成一个N*N的矩阵,记为D。并令L...
Besides, fuzzy kernel clustering methods are presented as extensions of kernel K-means clustering algorithm. Introduction Unsupervised data analysis using clustering algorithms provides a useful tool to explore data structures. Clustering methods [1], [2] have been addressed in many contexts and ...
The self-tuning spectral clustering is shown to extract and reveal required information from laboratory and clinical patient data which most helpful to assist physicians in increasing the accuracy of CKD identification before reach a severe stage. The clustering results are applying to machine learning ...
Which is the best (fastest) algorithm for... Learn more about k-means, silhouette, dunn index, davies bouldin index Statistics and Machine Learning Toolbox
Spectral clustering is a widely used clustering algorithm based on the advantages of simple implementation, small computational cost, and good adaptability to arbitrarily shaped data sets. However, due to the lack of data protection mechanism in spectral clustering algorithm and the fact that the proce...