External validation indexes allow similarities between two clustering solutions to be quantified. With classical external indexes, it is possible to quantify how similar two disjoint clustering solutions are, where each ...

Clustering validation indexes are intended to assess the goodness of clustering results. Many methods used to estimate the number of clusters rely on a validation index as a key element to find the correct answer. This paper ...

One of the most challenging aspects of clustering is validation, which is the objective and quantitative assessment of clustering results. A number of different relative validity criteria have been proposed for the validation ...

Clustering quality or validation indices allow the evaluation of the quality of clustering in order to support the selection of a specific partition or clustering structure in its natural unsupervised environment, where ...

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering ...

Clustering is a well-established technique for segmentation. However, clustering validation is rarely used for this purpose. In this work we adapt a clustering validation method, Clustering Stability (CS), to automatically ...

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is ...

In this paper the Optimized Vector and Marginal Median Self-Organizing Map (OVMMSOM) was proposed as a new method of train Self-Organizing Maps (SOM). This variant is based on order statistics, Marginal Median SOM (MMSOM) ...