Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41132
Title: Identifying clusters from positive data
Authors: Case, J.
Jain, S. 
Martin, E.
Sharma, A.
Stephan, F. 
Issue Date: 2004
Source: Case, J.,Jain, S.,Martin, E.,Sharma, A.,Stephan, F. (2004). Identifying clusters from positive data. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) 3264 : 103-114. ScholarBank@NUS Repository.
Abstract: The relationship between natural topological properties and clusterability has been investigated. The clusterability of a class does not depend on the decision which numbering of the class is used as a hypothesis space for the clusterer. The Turing degrees of maximal oracles which permit to solve all computationally interactable aspects of clustering are determined. It is shown that some oracles are trivial in the sense that they do not provide any useful information for clustering at all.
Source Title: Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
URI: http://scholarbank.nus.edu.sg/handle/10635/41132
ISSN: 03029743
Appears in Collections:Staff Publications

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