One of the problems with existing clustering methods is that the interpretation of clusters may be difficult. Two different approaches have been used to solve this problem: conce...
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Abstract--A method for explaining results of a regressionbased classifier is proposed. The data is clustered using a metric extracted from the classifier. This way, clusters found ...
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Domain experts are frequently interested to analyze multiple related spatial datasets. This capability is important for change analysis and contrast mining. In this paper, a novel ...