Exploring efficient attribute prediction in hierarchical clustering Export

@misc{citeulike:236233, abstract = {. This work explores the feasibility of constructing hierarchical clusterings minimizing the expected cost of exploiting these clusterings for a prediction task. Particularly, we focus on gaining efficiency by means of reducing the number of features used to describe each node in the hierarchy. To explore a number of different hierarchical clusterings we use the Isaac clustering system, which can select subsets of features at each node of the hierarchy and also, allows to bias the clustering...}, author = {Talavera, L.}, citeulike-article-id = {236233}, citeulike-linkout-0 = {http://citeseer.ist.psu.edu/talavera98exploring.html}, citeulike-linkout-1 = {http://citeseer.lcs.mit.edu/talavera98exploring.html}, citeulike-linkout-2 = {http://citeseer.ifi.unizh.ch/talavera98exploring.html}, citeulike-linkout-3 = {http://citeseer.comp.nus.edu.sg/talavera98exploring.html}, keywords = {clustering, feature, selection}, posted-at = {2005-06-24 20:56:52}, priority = {2}, title = {Exploring efficient attribute prediction in hierarchical clustering}, url = {http://citeseer.ist.psu.edu/talavera98exploring.html}, year = {1998} }

TY - GEN ID - citeulike:236233 L3 - citeulike-article-id:236233 N2 - . This work explores the feasibility of constructing hierarchical clusterings minimizing the expected cost of exploiting these clusterings for a prediction task. Particularly, we focus on gaining efficiency by means of reducing the number of features used to describe each node in the hierarchy. To explore a number of different hierarchical clusterings we use the Isaac clustering system, which can select subsets of features at each node of the hierarchy and also, allows to bias the clustering... TI - Exploring efficient attribute prediction in hierarchical clustering KW - clustering KW - feature KW - selection AU - Talavera, L PY - 1998/// UR - http://citeseer.ist.psu.edu/talavera98exploring.html ER -