Advances made to the traditional clustering algorithms solve the various problems such as curse of dimensionality and sparsity of data for multiple attributes. The traditional H-K clustering algorithm ...

Data clustering is the process of placing data items into different groups (clusters) in such a way that items in a particular group are similar to each other and items in different groups are ...

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...