Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
Hierarchical clustering is used widely to organize data and search for patterns. Previous algorithms assume that the body of data being clustered is fixed while the algorithm runs...
H. Van Dyke Parunak, Richard Rohwer, Theodore C. B...
Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partiti...