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A study on parallel versus sequential relational fuzzy clustering methods
February 2011
Fel11
Relational Fuzzy Clustering is a recent growing area of study. New algorithms have been developed,as FastMap Fuzzy c-Means (FMFCM) and the Fuzzy Additive Spectral Clustering Method(FADDIS), for which it had been obtained interesting experimental results in the corresponding founding works. Since these algorithms are new in the context of the Fuzzy Relational clustering community, not many experimental studies are available. This thesis comes in response to the need of further investigation on these algorithms, concerning a comparative experimental study from the two families of algorithms: the parallel and the sequential versions. These two families of algorithms differ in the way they cluster data. (...) The algorithms are studied in their effectiveness on retrieving good cluster structures by analysing the quality of the partitions as well as the determination of the number of clusters by applying several validation measures (...)
M. Sc. dissertation
Rui Felizardo
Susana Nascimento
Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa
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http://run.unl.pt/handle/10362/5663
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Rui Felizardo, A study on parallel versus sequential relational fuzzy clustering methods, Susana Nascimento (superv.), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (http://run.unl.pt/handle/10362/5663), February 2011.
<b>Rui Felizardo</b>, <u>A study on parallel versus sequential relational fuzzy clustering methods</u>, <a href="/people/members/view.php?code=4d69262d034cb8174d039bea8d970836" class="supervisor">Susana Nascimento</a> (superv.), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (<a href="http://run.unl.pt/handle/10362/5663" target="_blank">url</a>), February 2011.
@mastersthesis {Fel11, author = {Rui Felizardo}, title = {A study on parallel versus sequential relational fuzzy clustering methods}, school = {Faculdade de Ci{\^e}ncias e Tecnologia, Universidade Nova de Lisboa}, note = {Susana Nascimento (superv.); }, url = {http://run.unl.pt/handle/10362/5663}, abstract = {Relational Fuzzy Clustering is a recent growing area of study. New algorithms have been developed,as FastMap Fuzzy c-Means (FMFCM) and the Fuzzy Additive Spectral Clustering Method(FADDIS), for which it had been obtained interesting experimental results in the corresponding founding works. Since these algorithms are new in the context of the Fuzzy Relational clustering community, not many experimental studies are available. This thesis comes in response to the need of further investigation on these algorithms, concerning a comparative experimental study from the two families of algorithms: the parallel and the sequential versions. These two families of algorithms differ in the way they cluster data. (...) The algorithms are studied in their effectiveness on retrieving good cluster structures by analysing the quality of the partitions as well as the determination of the number of clusters by applying several validation measures (...)}, keywords = {Relational data, Relational fuzzy clustering, Fuzzy additive spectral clustering,Number of clusters, Validation indices}, month = {February}, year = {2011}, }
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