COBWEB is an incremental algorithm for hierarchical conceptual clustering. It organizes observations into a classification tree whose nodes summarize probabilistic patterns over attributes and can support prediction of missing values or classes.
An incremental system for hierarchical conceptual clustering. COBWEB was invented by Professor Douglas H. Fisher, currently at Vanderbilt University. COBWEB incrementally organizes observations into a classification tree. Each node in a classification tree represents a class (concept) and is labeled by a probabilistic concept that summarizes the attribute-value distributions of objects classified under the node. This classification tree can be used to predict missing attributes or the class of a new object.