Description: 聚类分析技术有着广泛应用.因为在对图像进行聚类分析时,通常缺少可资利用的先验知识,所以需要采用无监督的聚类算法.为了适应图像检索的需要,提出了一种新型的无监督聚类方法,即根据离群点信息来自动确定聚类算法的终止时机.此方法还弥补了现有聚类算法在离群点识别、使用上的缺欠.为验证其可行性,用其改进了CURE和ROCK两个经典算法.实验表明,改进后的两个算法都能自动终止,并能取得优于以往的聚类效果. -clustering analysis techniques have wide application. In the image clustering analysis, usually available to the lack of a priori knowledge, Therefore, the need for unsupervised clustering algorithm. To meet the needs of image retrieval, propose a novel unsupervised clustering method, That is, according to information outliers automatically clustering algorithm to determine the time of termination. This method also makes up for in the existing clustering algorithm outliers identification, the use of the shortcomings. To test its feasibility. use its improved CURE ROCK and two classical algorithm. Experiments show that The two improved algorithm can automatically terminated and can be made better than the previous clustering effect. Platform: |
Size: 1467 |
Author:陈一 |
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Description: 中心点漂移是一种非监督聚类算法（与k-means算法相似，但应用范围更广些),可用于图像分割，基于Matlab实现的源码。
MedoidShift is a unsupervised clustering algorithm(similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code. Platform: |
Size: 37357 |
Author:陈明 |
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Description: JAVA 本程序所实现的功能为对数据进行无监督的学习，即聚类算法-JAVA the procedures for the functions of data unsupervised learning, clustering algorithm Platform: |
Size: 7168 |
Author:puxx |
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Description: 聚类分析技术有着广泛应用.因为在对图像进行聚类分析时,通常缺少可资利用的先验知识,所以需要采用无监督的聚类算法.为了适应图像检索的需要,提出了一种新型的无监督聚类方法,即根据离群点信息来自动确定聚类算法的终止时机.此方法还弥补了现有聚类算法在离群点识别、使用上的缺欠.为验证其可行性,用其改进了CURE和ROCK两个经典算法.实验表明,改进后的两个算法都能自动终止,并能取得优于以往的聚类效果. -clustering analysis techniques have wide application. In the image clustering analysis, usually available to the lack of a priori knowledge, Therefore, the need for unsupervised clustering algorithm. To meet the needs of image retrieval, propose a novel unsupervised clustering method, That is, according to information outliers automatically clustering algorithm to determine the time of termination. This method also makes up for in the existing clustering algorithm outliers identification, the use of the shortcomings. To test its feasibility. use its improved CURE ROCK and two classical algorithm. Experiments show that The two improved algorithm can automatically terminated and can be made better than the previous clustering effect. Platform: |
Size: 1024 |
Author: |
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Description: 无监督聚类的VC源码。。数据挖掘中的一种经典聚类算法-Unsupervised clustering of the VC source. . Data Mining in a classic clustering algorithm Platform: |
Size: 308224 |
Author:xhy |
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Description: 中心点漂移是一种非监督聚类算法（与k-means算法相似，但应用范围更广些),可用于图像分割，基于Matlab实现的源码。
MedoidShift is a unsupervised clustering algorithm(similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code.-Center drift is a non-supervised clustering algorithm (k-means algorithm with the similar, but more a wider range of applications), can be used for image segmentation, based on the realization of the source Matlab. MedoidShift is a unsupervised clustering algorithm (similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code. Platform: |
Size: 36864 |
Author:陈明 |
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Description: 这是一篇详细介绍人脸检测与语音驱动口型的文章，其中使用了高斯混合模型采取了无监督聚类的方法，希望对你有用。-This is a detailed introduction Face Detection and voice-driven I-type article, which uses the Gaussian mixture model taken unsupervised clustering method, in the hope that useful to you. Platform: |
Size: 251904 |
Author: kellan |
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Description: 用JAVA语言实现的经典聚类算法k-means，聚类与分类不同，它是无监督的过程，-JAVA language used to achieve a classic clustering algorithm k-means, clustering and classification of different, it is the unsupervised process, Platform: |
Size: 8192 |
Author:刘年 |
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Description: 无监督聚类算法,能够自动聚类,不必预先给出类数,聚类精度好于常用的聚类算法.-Unsupervised clustering algorithm, can automatically cluster, do not have to give in advance the number of categories, clustering accuracy of better than commonly used clustering algorithm. Platform: |
Size: 4096 |
Author:李好 |
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Description: 文本聚类，VC编程实现，作为一种无监督的机器学习方法，聚类由于不需要训练过程，以及不需要预先对文档手工标注类别，因此具有一定的灵活性和较高的自动化处理能力-Text Clustering, VC programming, as an unsupervised machine learning method, clustering by eliminating the need for the training process, and do not need to manually pre-marked on the document type, and therefore a higher degree of flexibility and automation of processing power Platform: |
Size: 16384 |
Author:chengbo |
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Description: The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data.
Reference: C. Bouveyron, S. Girard and C. Schmid, High-Dimensional Data Clustering, Computational Statistics and Data Analysis, to appear, 2007-The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data.
Reference: C. Bouveyron, S. Girard and C. Schmid, High-Dimensional Data Clustering, Computational Statistics and Data Analysis, to appear, 2007 Platform: |
Size: 50176 |
Author:tra ba huy |
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Description: isodata是个重要的非监督聚类算法，本文件提供了isodata的c++描述-isodata is an important unsupervised clustering algorithm, this paper provides a isodata of c++ description Platform: |
Size: 10240 |
Author:wistmm |
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Description: 本程序用c编写，主要用于对遥感图像进行聚类（非监督分类）。-This programme is used to for clustering images (unsupervised classifciation) Platform: |
Size: 3072 |
Author:李会利 |
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Description: 基于混合高斯模型（GMM）的无监督聚类算法，希望对大家有帮助-Based on Gaussian mixture model (GMM) unsupervised clustering algorithm, I hope it would have help to you！ Platform: |
Size: 320512 |
Author:姜赫 |
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Description: 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. Platform: |
Size: 10240 |
Author:王梓瑞 |
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Description: K-meansK均值聚类在无监督的情况下选择图像特征的算法-K-meansK means clustering in the case of unsupervised image feature selection algorithm Platform: |
Size: 46080 |
Author:renli |
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Description: In statistics, a mixture model is a probabilistic model for density estimation using a mixture distribution. A mixture model can be regarded as a type of unsupervised learning or clustering. Mixture models should not be confused with models for compositional data, i.e., data whose components are constrained to sum to a constant value (1, 100 , etc.). Platform: |
Size: 40960 |
Author:alice |
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Search - unsupervised clustering