Cobweb (clustering)


COBWEB is 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 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.
There are four basic operations COBWEB employs in building the classification tree. Which operation is selected depends on the category utility of the classification achieved by applying it. The operations are:
COBWEB:
Input: A COBWEB node root, an instance to insert record
if root has no children then
children :=
newcategory \\ adds child with record’s feature values.
insert \\ update root’s statistics
else
insert
for child in root’s children do
calculate Category Utility for insert,
set best1, best2 children w. best CU.
end for
if newcategory yields best CU then
newcategory
else if merge yields best CU then
merge
COBWEB
else if split yields best CU then
split
COBWEB
else
COBWEB
end if
end