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

一本将基于近邻传播算法的半监督聚类的算方法书.对于聚类研究的很有帮助-Abstract: 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 a

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

机器学习的范畴，包括SVMs (based on libsvm), k-NN, random forests, decision trees。可以对任意的数据操作-Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. It also performs feature sel