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这是用matlab编的谱聚类程序，该方法能有效的用于数据分类。,This is a matlab procedures for the spectral clustering.The method is effective for data classification.
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谱聚类和SVM相结合的图像分割程序,这是用matlab编的谱聚类程序，该方法能有效的用于数据分类。-This is a matlab procedures for the spectral clustering.The method is effective for data classification.
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基于无监督学习的谱聚类算法的文本的聚类分类。-Unsupervised Learning Based on spectral clustering algorithm for text clustering classification.
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快速谱聚类算法的实现，使用R语言,在linux下运行-fast approximate spectral clustering
implemented with K-means complete with R
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谱聚类算法综述，一篇关于普聚类的文章，有兴趣的可以下来看看。-Summary of spectral clustering algorithm, a cluster of articles on general, are interested can look down.
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三种典型的基于图分割的谱聚类方法比较，模式识别方向相关论文。-Three typical graph-based segmentation of spectral clustering comparison, pattern recognition, the direction of relevant papers.
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一种用于聚类分析的谱聚类方法（Matlab版），可以有效，快速的对多维样本数据进行聚类划分-For cluster analysis of spectral clustering methods can be effective, fast multi-dimensional sample data clustering divided
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谱聚类算法，与传统聚类相比，有任意形状的样本空间上聚类且收敛于全局最优解的优点-Spectral clustering algorithm, compared with the traditional clustering, the sample space of an arbitrary shape clustering and convergence to global optimal solution the advantages of
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机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with
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In multivariate statistics and the clustering of data, spectral clustering[1] techniques make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions. The simila
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A Tutorial on Spectral Clustering
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谱聚类综述 谱聚类综述 -spectral clustering overview
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谱聚类算法，基于非欧几里德几何结构的算法。-Spectral Clustering
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matlab-Spectral Clustering
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机器学习的各种算法，与实现 如谱分析 ，随机森林，分类器，线性分类器-machine learning and artifical intelligence spectrum anysis ramdom forest and linear classification
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2015数学建模B题，包括了人工智能很多知识，有谱聚类，多流形学习，人脸识别，以及稀疏子空间聚类。其中的英文参考文献很有价值。-2015 mathematical modeling of B problems, including the artificial intelligence of a lot of knowledge, a spectral clustering, manifold learning, face recognition, as well as sparse subsp
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