The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
Mark K. Goldberg, Mykola Hayvanovych, Malik Magdon...
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
Clustering or co-clustering techniques have been proved useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. ...