Abstract In data clustering, many approaches have been proposed. For example, K-means method and hierarchical method. A problem is in effect by initial value and criterion to comb...
In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and...
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Background: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage o...
Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V...
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...