Search - subspace clustering

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[Industry research] High DL : 0: This paper presents a clustering approach which estimates the specific subspace and the intrinsic dimension of each class. Our approach adapts the Gaussian mixture model framework to high-dimensional data and estimates the parameters which best fit the data. We obtain a robust clustering method called High- Dimensional Data Clustering (HDDC). We apply HDDC to locate objects in natural images in a probabilistic framework. Experiments on a recently proposed database demonstrate the effectiveness of our clustering method for category localization.
Date : 2025-07-06 Size : 189kb User : tra ba huy
[Algorithm] MAFIA DL : 0: Adaptive Grids for Clustering Massive Data Sets - MAFIA. It is a subspace clustering algorithm.-Adaptive Grids for Clustering Massive Data Sets- MAFIA. It is a subspace clustering algorithm.
Date : 2025-07-06 Size : 134kb User : volkanbaykan
[Algorithm] CLTree DL : 0: Clustering through Decision Tree Construction - CLTree - A subspace clustering algorithm.-Clustering through Decision Tree Construction- CLTree- A subspace clustering algorithm.
Date : 2025-07-06 Size : 87kb User : volkanbaykan
[Algorithm] ORCLUS DL : 0: Finding Generalized Projected Clusters in High Dimensional Spaces - ORCLUS - A subspace clustering algorithm.-Finding Generalized Projected Clusters in High Dimensional Spaces- ORCLUS- A subspace clustering algorithm.
Date : 2025-07-06 Size : 131kb User : volkanbaykan
[Algorithm] PROCLUS DL : 0: Fast Algorithms for Projected Clustering - PROCLUS - a traditional subspace clustering algorithm for high dimensional data-Fast Algorithms for Projected Clustering- PROCLUS- a traditional subspace clustering algorithm for high dimensional data
Date : 2025-07-06 Size : 128kb User : volkanbaykan
[Algorithm] ENCLUS DL : 0: Entropy Based Subspace Clustering for Mining Data - ENCLUS - a new version of PROCLUS algorithm for clustering high dimensional data set.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorithm for clustering high dimensional data set.
Date : 2025-07-06 Size : 130kb User : volkanbaykan
[Algorithm] COSA DL : 0: Clustering objects on subsets of attributes - COSA - a subspace clustering algorithm.-Clustering objects on subsets of attributes- COSA- a subspace clustering algorithm.
Date : 2025-07-06 Size : 401kb User : volkanbaykan
[Algorithm] sdm04-subclu DL : 0: Subspace based clustering mechanism comparison
Date : 2025-07-06 Size : 230kb User : amila banuka
[AI-NN-PR] DENCOS-PPT DL : 0: DENCOS Subspace Clustering for PPT
Date : 2025-07-06 Size : 1.15mb User : svelu
[AI-NN-PR] A-survey-on-subspace-clustering--pattern-based-cl DL : 0: Clustering high-dimensional data A survey on subspace clustering, pattern-based clustering, and correlation clustering-Clustering high-dimensional data A survey on subspace clustering, pattern-based clustering, and correlation clustering
Date : 2025-07-06 Size : 1.47mb User : 蒋华荣
[Windows CE] Density-Conscious-Subspace-Clustering-for-High-Di DL : 0: Density Conscious Subspace Clustering for High-Dimensional Data
Date : 2025-07-06 Size : 2.14mb User : 蒋华荣
[matlab] motion_segmentation_subspace DL : 0: 基于子空间方法的运动分割技术研究，包GPCA with spectral clustering，RANSAC Local Subspace Affinity (LSA)，三种方法-Motion segmentation technique based on subspace method, including the GPCA with spectral clustering, RANSAC Local Subspace Affinity (LSA)
Date : 2025-07-06 Size : 20kb User : liu
[Special Effects] kmean DL : 0: 包括K-均值聚类算法的思想介绍，kmeans的MATLAB代码，c语言代码、c++代码。-Including the K-means clustering algorithm introduced the idea, kmeans of MATLAB code, c language code, c++ code.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorithm for clustering high dimensional data set.
Date : 2025-07-06 Size : 1.08mb User : 陈老师
[Mathimatics-Numerical algorithms] d DL : 0: 聚类分析是数据挖掘研究领域中一个非常活跃的研究课题) 本文重点分析了高维度数据的自动子空间聚类算法 -Cluster analysis is data mining a very active field of research topic) This paper focuses on high-dimensional data subspace clustering algorithm automatically
Date : 2025-07-06 Size : 58kb User : sdc
[Mathimatics-Numerical algorithms] e DL : 0: ：聚类分析是数据挖掘研究领域中一个非常活跃的研究课题) 本文重点分析了高维度数据的自动子空间聚类算法-: Cluster analysis is data mining a very active field of research topic) This paper focuses on high-dimensional data subspace clustering algorithm automatically
Date : 2025-07-06 Size : 194kb User : sdc
[Mathimatics-Numerical algorithms] SubLppClustering_upload DL : 0: 模糊子空间聚类算法包括评价指标模拟数据集等参考文献 G.J. Gan and J.H. Wu, A convergence theorem for the fuzzy subspace clustering (FSC) algorithm, Pattern Recognition, vol.41, pp.1939-1947, 2008.-fuzzy subspace clustering algorithms reference: G.J. Gan and J.H. Wu, A convergence theorem for the fuzzy subspace clustering (FSC) algorithm, Pattern Recognition, vol.41, pp.1939-1947, 2008.
Date : 2025-07-06 Size : 10kb User : dzh
[Other] Sparse-Subspace-Clustering DL : 0: Sparse Subspace Clustering
Date : 2025-07-06 Size : 2.71mb User : Soufi
[DataMining] sparse-subspace-clustering DL : 0: 关于稀疏子空间聚类的算法程序实现，及对应的论文，matlab源码实现。-On sparse subspace clustering algorithm procedures, and the corresponding paper, matlab source code.
Date : 2025-07-06 Size : 9.58mb User : xiazhi
[AI-NN-PR] clustering-master DL : 0: 稀疏子空间聚类的算法程序实现，用Matlab实现的SSC算法。-Sparse subspace clustering algorithm procedures to achieve, SSC algorithm implemented with Matlab.
Date : 2025-07-06 Size : 9kb User : 姜文
[matlab] local-best-fit-flats-clustering DL : 0: 可实现局部最优近似平面数据聚类，该聚类方法是一种常用的子空间聚类方法，文章作者没有给出相应的源码，这里提供给大家。经过测试可以实现数据聚类，但是对人脸数据集extended yale B效果不理想。参考文献：Teng Zhang, Arthur Szlam, Yi Wang, et al. Hybrid linear modeling via local best-fit flats [J]. International Journal of Computer Vision, 2012, 100: 217-240.-This program can realize local best fit flats subspace clustering. Local best fit flats subspace clustering is one of the commonly used subspace clustering methods. The authors of the paper didn t present the source code and here it is given. The program is tested and it can be used to realize data clustering but its effect is not satisfying in clustering data extended yale B face . Reference: Teng Zhang, Arthur Szlam, Yi Wang, et al. Hybrid linear modeling via local best-fit flats [J]. International Journal of Computer Vision, 2012, 100: 217-240.
Date : 2025-07-06 Size : 2kb User : 宋昱

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