Description: 最新AP聚类算法以及演示程序，算法内容参照affinity appropagation in science。-AP latest clustering algorithm as well as the demo program, algorithm reference content affinity appropagation in science. Platform: |
Size: 5120 |
Author:lilan |
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Description: AP是在数据点的相似度矩阵的基础上进行聚类.对于规模很大的数据集,AP算法是一种快速、有效的聚类方法,这是其他传统的聚类算法所不能及的,-A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this paper. AP takes as input measures of similarity between pairs of data points. AP is an efficient and fast clustering algorithm for large dataset compared with the existing clustering algorithms, such as K-center clustering. But for the datasets with complex cluster structures, it cannot produce good clustering results. It can improve the clustering performance of AP by using the priori known labeled data or pairwise constraints to adjust the similarity matrix. Experimental results show that such method indeed reaches its goal for complex datasets, and this method outperforms the comparative methods when there are a large number of pairwise constraints. Platform: |
Size: 375808 |
Author:lilan |
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Description: 一种新的聚类算法，被翻译为“吸引力传播聚类”，希望对研究模式识别的同学有帮助，谢谢啦-A new clustering algorithm is provided, which is called the Affinity Propagation Clustering. I hope it is helpful for people major in PR. Thank you for your attention. Platform: |
Size: 418816 |
Author:zhangjing |
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Description: Semi-supervised Affinity Propagation clustering.基于AP聚类的半监督学习算法。-The programs of semi-supervised AP are suitable for the person who has interests in studying or improving AP algorithm,
and then the semi-supervised AP may be an example for reference. Platform: |
Size: 17408 |
Author:troywang |
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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 |
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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 |
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Description: 07年发到Science上的关于聚类的文章《Clustering by passing messages between data points》的聚类算法--紧邻传播算法的源代码！-The source code of the clustering algorithm of <<Clustering by passing messages between data points>> Platform: |
Size: 4096 |
Author:duconghui |
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Description: Affinity Propagation(AP)聚类方法的原始版本，并附加了在Science杂志上的原文献，对于研究AP算法的人会有很多参考价值。-The original version of the AP clustering method. Attached the original documents in the journal Science,it will have a lot of reference value for studying the AP algorithm. Platform: |
Size: 423936 |
Author:soongz |
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Description: 相似性传播聚类，不需要初始化聚类中心，聚类速度优于k-maans，k-centers等聚类算法-Affinity propagation clustering, do not need to initialize the cluster center, cluster velocity than k-maans, k-centers clustering algorithm, etc. Platform: |
Size: 5120 |
Author:幸福 |
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Description: 本程序为仿射传播聚类的算法，相比较于K均值聚类不需要确定聚类个数，且对初始聚类中心不敏感-This procedure for affinity propagation clustering algorithm, compared to K-means clustering is not required to determine the number of clusters, and is not sensitive to the initial cluster centers Platform: |
Size: 21504 |
Author:付幸 |
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Search - Affinity Propagation clustering