clusteringoverview
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| - | ===== The Clustering Problem ====== | + | ====== The Clustering Problem ======= |
| Clustering is a process that groups a set of objects into several subsets which are called clusters. The goal of the clustering process is to define the clusters in a way that each object and the object that is not more similar to another object are member of the same cluster. In other words, objects within a cluster should be most similar while objects of different clusters should be most different to each other. | Clustering is a process that groups a set of objects into several subsets which are called clusters. The goal of the clustering process is to define the clusters in a way that each object and the object that is not more similar to another object are member of the same cluster. In other words, objects within a cluster should be most similar while objects of different clusters should be most different to each other. | ||
| - | There are many purposes for performing clustering such as data reduction or hypothesis generation. Subsection describes the different purposes of clustering. | + | There are many purposes for performing clustering such as data reduction or hypothesis generation. Subsection [[clusteringpurposes|Purpose of Clustering]]describes the different purposes of clustering. |
| - | There are several categories of clustering algorithms including partitioning clustering algorithms, hierarchical clustering algorithms, density-based clustering algorithms, or grid-based clustering algorithms. This dissertation sketches partitioning clustering algorithms and hierarchical clustering algorithms in the succeeding subsections because the clustering algorithm presented in chapter is a combined algorithm consisting of a partitioning clustering algorithm and a hierarchical clustering algorithm. | + | There are several categories of clustering algorithms including partitioning clustering algorithms, hierarchical clustering algorithms, density-based clustering algorithms, or grid-based clustering algorithms. This dissertation sketches partitioning clustering algorithms and hierarchical clustering algorithms in the succeeding subsections because the clustering algorithm presented in chapter \ref{chad} is a combined algorithm consisting of a partitioning clustering algorithm and a hierarchical clustering algorithm. |
| This section concludes with a subsection discussing quality measure of clustering. Especially, that subsection focusses on the quality measures used in the experiments of of the approach of this dissertation. | This section concludes with a subsection discussing quality measure of clustering. Especially, that subsection focusses on the quality measures used in the experiments of of the approach of this dissertation. | ||
clusteringoverview.1497170975.txt.gz · Last modified: 2017/06/11 10:49 by mgoller
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