We propose a single, practical algorithm to construct strong coresets for a large class of hard and soft clustering problems based on Bregman divergences. This class includes hard clustering with popular distortion measures such as the Squared Euclidean distance, the Mahalanobis distance, KL-divergence...
We propose a single, practical algorithm to construct strong coresets for a large class of hard and soft clustering problems based on Bregman divergences. This class includes hard clustering with popular distortion measures such as the Squared Euclidean distance, the Mahalanobis distance, KL-divergence...
In this paper, we suggest a new technique for soft clustering of multidimensional data. It is based on a new convex voting model, where each voter chooses
1) soft clustering 软聚类1. Inspired by soft clustering thought,a intelligent feature mode of days load data extracting method is proposed based on the mutual offset of fuzzy c-means clustering arithmetic and Kohonen self organization feature . 以软聚类思想为指导,通过模糊C均值聚类算法及Kohonen自...
We show that by applying the soft clustering method where a document is assigned to several significant clusters, we can improve the performance of hard clustering method while still reducing the number of considered documents to a reasonable size. 展开 ...
typically suffer from difficulties in tailoring the morphology and pore structures, the hard-...
In this method, clusters of similar elements are tried to be created; pixels of images are clustered on three different axes based on RGB. The clustering is implemented by a function, which minimizes the distance between the data points and the centroid or any central tendency of the cluster....
[Advances in Soft Computing] Soft Computing as Transdisciplinary Science and Technology Volume 29 || Clustering Ants with Self-Synchronized Interaction Soft computing is currently causing a paradigm shift (breakthrough) in science and technology.The stage for the Fifth IEEE/ACM International Conference ...
Special issue on soft computing and intelligent systems: Tools, techniques and applications (LDA). Microblogging services like Twitter have gained immense popularity. In [17], a framework for event detection is described using recursive hierarchical clustering. The different levels of the hierarchy repre...
For the analysis of microarray data, clustering techniques are frequently used. Most of such methods are based on hard clustering of data wherein one gene (or sample) is assigned to exactly one cluster. Hard clustering, however, suffers from several drawbacks such as sensitivity to noise and in...