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Abstract—Clustering face images according to their latent identity has two important applications: (i) grouping a collection of face images when no external labels are associated with images, and (ii) indexing for efficient large scale face retrieval. The clustering problem is composed of two key parts: representation and similarity metric for face images, and choice of the partition algorithm. We first propose a representation based on ResNet, which has been shown to perform very well in image classification problems. Given this representation, we design a clustering algorithm, Conditional Pairwise Clustering (ConPaC), which directly estimates the adjacency matrix only based on the similarities between face images. This allows a dynamic selection of number of clusters and retains pairwise similarities between faces. ConPaC formulates the clustering problem as a Conditional Random Field (CRF) model and uses Loopy Belief Propagation to find an approximate solution for maximizing the posterior probability of the adjacency matrix. Experimental results on two benchmark face datasets (LFW and IJB-B) show that ConPaC outperforms well known clustering algorithms such as k-means, spectral clustering and approximate Rank-order. Additionally, our algorithm can naturally incorporate pairwise constraints to work in a semi-supervised way that leads to improved clustering performance. We also propose an k-NN variant of ConPaC, which has a linear time complexity given a k-NN graph, suitable for large datasets. Index Terms—face clustering, face representation, Conditional Random Fields, pairwise constraints, semi-supervised clustering.

高光谱遥感图像模糊c均值聚类算法的matlab实现

RFM集群

基于密度的聚类算法，含测试数据，MATLAB版本，可以直接运行。

层次聚类：层次聚类 划分聚类法：Kmeans算法 基于密度的聚类：DBSCAN的概念

使用python进行dbscn聚类，同时做了可视化，参数自己调，数据集改下路径导进去就好了1111111111111111

二维人工数据集：6个 数据 xxx.txt 标签 xxx_cl.txt UCI真实数据集：10个 数据 xxx.txt 标签 xxx_label.txt

【程序老媛出品，必属精品，亲测校正，质量保证】 资源名：MATLAB实现模糊聚类算法 程序源码.zip 资源类型：程序源代码 源码说明： MATLAB实现按照模糊聚类法对测试集进行分类的程序，包含完整源码和注释 非常适合借鉴学习 适合人群：新手及有一定经验的开发人员

模糊C均值聚类算法代码，实现数据聚类，机器学习代码的一部分。