Search - 聚类稀疏

[Other resource] gmeans

Description: gmeans-- Clustering with first variation and splitting 文本聚类算法Gmeans ,使用了3种相似度函数,cosine,euclidean ,KL.文本数据使用的是稀疏矩阵形式. -gmeans clustering with first variation and splitting Gmeans,a text clustering algorithm, uses 3 functions,cosine,euclidean and KL in similarity measuring.Text data are described by sparse matrix.
Platform: | Size: 71569 | Author: 修宇 | Hits:

[AI-NN-PR] gmeans

[Other] Onemethodofabstractingcharacters

Description: 介绍了一种非常实用的特征提取新方法，针对稀疏核主成分分析方法在特征提取中的不足, 提出了一种基于核K- 均值聚类的稀疏核主成分分析( Sparse KPCA) 的特征提取方法用于说话人识别。-Introduced a very useful new method of feature extraction for Sparse Kernel Principal Component Analysis in Feature Extraction of the lack of a kernel-based K-means clustering of sparse kernel principal component analysis (Sparse KPCA) of the feature extraction methods for speaker recognition.
Platform: | Size: 122880 | Author: 毋桂萍 | Hits:

[Mathimatics-Numerical algorithms] GraphPrj

Description: 针对大规模稀疏无向图开发的聚类算法。附带测试页面-this program is supposed to embark on the undiret graph clustering issue.
Platform: | Size: 141312 | Author: zhangxucheng | Hits:

[3D Graphic] SFMtoolsInstallDoc

Description: 文介绍了如何使用Bundler来根据图片得到相机参数以及一些空间点云数据，得到的数据将能够运用在3D重建中。利用Bundler可以得到较为稀疏的点云（point clouds）数据。如果需要得到更密集的点，可以使用Yasutaka Furukawa博士写的另外一个非常强大的软件包，称为PMVS2。一种比较常见的途径是使用Bundler来得到相机参数，然后使用Bundle2PMVS程序，将生成结果转换为PMVS2的输入，然后使用PMVS2来得到更密集的点云。另外，读者们可能会对另外一个同样由Furukawa博士开发的实用工具——CMVS感兴趣，CMVS是一个场景聚类程序，在使用PMVS2前可以使用它来进行一些预处理。 -Photogrammetry 3D reconstruction using Bundler and PMVS2 and CMVS
Platform: | Size: 5120 | Author: binbin | Hits:

[Mathimatics-Numerical algorithms] ItemClusteringRecomAlg

Description: 针对传统推荐算法的数据稀疏性问题和推荐准确性问题，提出基于粒子群优化的项聚类推荐算法。采用粒子群优化算法产生聚类中心，在此基础上搜索目标项目的最近邻居，并产生推荐，从而提高了传统聚类算法的推荐准确性及响应速度。实验表明改进的项聚类协同过滤算法能有效提高推荐精度-Aiming at the problems that the data are sparse and the results are not accurate in traditional recommendation algorithms, this paper proposes an item clustering recommendation algorithm based on Particle Swarm Optimization(PSO) algorithm. It uses PSO to engender the cluster centers, calculates the similarity between target item and cluster centers to search the nearest neighbors of target item, and gains a recommendation, so that it improves the accuracy and the real-time performance. Experimental results indicate that the algorithm can effectively improve the accuracy of the recommendation system
Platform: | Size: 366592 | Author: ming | Hits:

[matlab] matlab-functions

Description: ：在有限区域内分布的稀疏不均的、具有一定分布结构的海量数据集的高效、高精度聚类问题是一个尚未完全圆满解决的难题。针对Affinity Propagation 聚类算法(AP)的不足之处，提出了两个改进型的聚类算法-n limited areas of uneven distribution of sparse, has certain distribution structure of the mass datasets of high efficiency, high precision together Problem is a perfectly solved problem has not yet completely. For Affinity Propagation clustering algorithm (AP) of the deficiencies, Put forward the two improved version of the clustering algorithm
Platform: | Size: 9216 | Author: 李会清 | Hits:

[matlab] affiniyPropagation_afunctions

Description: 在有限区域内分布的稀疏不均的、具有一定分布结构的海量数据集的高效、高精度聚类问题是一个尚未完全圆满解决的难题。针对Affinity Propagation 聚类算法(AP)的不足之处，提出了两个改进型的聚类算法-In a limited area of uneven distribution of sparse, has certain distribution structure of the mass datasets of high efficiency, high precision together Problem is a perfectly solved problem has not yet completely. For Affinity Propagation clustering algorithm (AP) of the deficiencies, Put forward the two improved version of the clustering algorithm
Platform: | Size: 87040 | Author: 李会清 | Hits:

[Speech/Voice recognition/combine] mean-K-KPCA

Description: 通过核 K- 均值聚类的方法对语音帧进行聚类 , 由于聚类的中心能够很好地代表类内的特征, 用中心样本帧取代该类, 减少了核矩阵的维数, 然后再采用稀疏 KPCA方法对核矩阵进行特征提取。-Through the nuclear K-means clustering method for clustering of speech frames, the cluster center can be a good representative of the class characteristics of the sample frame to replace the class with the center, reducing the dimension of the nuclear matrix, and then use Sparse KPCA method for feature extraction of the nuclear matrix.
Platform: | Size: 185344 | Author: piano | Hits:

[Windows Develop] CSR_denoise

Description: 一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果-a image denoising method with structral clustering and sparse representation, has good effect .
Platform: | Size: 1668096 | Author: wangchangpeng | Hits:

[matlab] clustering_coefficients

Description: 关于复杂网络的聚类系数算法，用matlab计算，矩阵为稀疏矩阵。-clustering_coefficients(A) returns the clustering coefficients for all vertices in A. The clustering coefficient is the ratio of the number of edges between a vertex s neighbors to the total possible number of edges between the vertex s neighbors.
Platform: | Size: 1024 | Author: 李涛 | Hits:

[Special Effects] CSR_Denoising

Description: Weisheng Dong and Xin Li. "Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering"基于聚类的图像稀疏去噪这篇论文的去噪代码。-Weisheng Dong and Xin Li. " Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering" Cluster-based image denoising paper sparse denoising code.
Platform: | Size: 585728 | Author: 王梦婕 | Hits:

[Graph program] 基于聚类稀疏描述的图像去噪

Description: 图像去噪是图像处理中一项典型的技术，在实际中该项技术有很多应用，因为现实中的数字图像在数字化和传输过程中常受到成像设备与外部环境噪声干扰等影响。图像本身具有很强的冗余特性，近年来，在图像处理中提出用冗余的字典来对图像进行稀疏描述，而应用稀疏描述的思想可以有效的对含噪图像去除噪声。
Platform: | Size: 1808504 | Author: 770314992@qq.com | Hits:

[matlab] CaiDengcode

Description: 浙大蔡登，何晓飞写的降维，特征选择等机器学习的源码包括：谱回归，降维，特征选择，主题模型，矩阵分解，稀疏编码，哈希，聚类，主动学习，矩阵学习。是一个很好的机器学习源码资料。-cCaideng s code for Machine learning,include Spectral regression : (a regression framework for efficient dimensionality reduction) Dimensionality reduction (Subspace learning) Feature selection Topic modeling and GMM Matrix factorization Sparse coding Hashing Clustering Active learning Ranking and Metric learning
Platform: | Size: 192512 | Author: 罗鹏 | Hits:

[matlab] ap-clustering

Description: 2007在science杂志发表的一种大数据处理的聚类算法仿射传播算法有普通版和稀疏矩阵两种-ap cluster
Platform: | Size: 9216 | Author: 王辛 | Hits:

[Other] SSC_test

Description: 稀疏表示凸优化低秩表示用于聚类分析 -sparse representing, convex optimization low rank representing
Platform: | Size: 337920 | Author: | Hits:

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