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BIRCH (balanced iterative reducing and clustering using hierarchies) is an algorithm used to perform connectivity-based clustering for large data-sets. [7] It is regarded as one of the fastest clustering algorithms, but it is limited because it requires the number of clusters as an input.
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).
OpenSSI is an open-source single-system image clustering system. It allows a collection of computers to be treated as one large system, allowing applications running on any one machine access to the resources of all the machines in the cluster.
Computer cluster, the technique of linking many computers together to act like a single computer; Data cluster, an allocation of contiguous storage in databases and file systems; Cluster analysis, the statistical task of grouping a set of objects in such a way that objects in the same group are placed closer together (such as the k-means ...
Open Cluster Framework (OCF) is a set of standards for computer clustering. The project started as a working group of the Free Standards Group , now part of the Linux Foundation . Original supporters included several computing companies and groups, including Compaq , Conectiva , IBM , Linux-HA , MSC Software , the Open Source Development Lab ...
In computer science, data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data, financial transactions etc. Data stream clustering is usually studied as a streaming algorithm and the objective is, given a sequence of points, to construct a good clustering of the stream, using a small amount of memory and time.
Kerrighed is an open source single-system image (SSI) cluster software project. The project started in October 1998 at the Paris research group The French National Institute for Research in Computer Science and Control. From 2006 to 2011, the project was mainly developed by Kerlabs. In January, 2012 the Linux clustering mission of Kerlabs was ...
In computer science, constrained clustering is a class of semi-supervised learning algorithms. Typically, constrained clustering incorporates either a set of must-link constraints, cannot-link constraints, or both, with a data clustering algorithm. A cluster in which the members conform to all must-link and cannot-link constraints is called a ...