{"id":{"repo_id":"wfu","oai_identifier":"oai:wakespace.lib.wfu.edu:10339/38565"},"canonical_url":"https://search.dev.ndltd.org/etd/wfu/oai:wakespace.lib.wfu.edu:10339/38565","repository":{"repo_id":"wfu","name":"Wake Forest University","base_url":"https://wakespace.lib.wfu.edu/oai/request"},"display":{"title":"Probabilistic Finite Mixture Clustering of Genetic Expression Microarray Data","abstract":"Exploratory cluster analysis of large data sets often implements k-means or hierarchical methods. These routines typically exhibit limitations which reduces the reliability of the results. Both assign observations to the one component for which its Euclidean distance from the center is smallest. Furthermore, these methods force a common variance in every dimension and do not permit covariances between dimensions. A final limitation is that these methods prohibit statistical inference.","abstract_html":"Exploratory cluster analysis of large data sets often implements k-means or hierarchical methods. These routines typically exhibit limitations which reduces the reliability of the results. Both assign observations to the one component for which its Euclidean distance from the center is smallest. Furthermore, these methods force a common variance in every dimension and do not permit covariances between dimensions. A final limitation is that these methods prohibit statistical inference.","abstract_has_math":false,"creators":["Higgins, Ixavier"],"institution":"Wake Forest University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013","date_published":"2013","updated_at":"2026-07-27T22:01:33Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10339/38565","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Higgins, Ixavier"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2013-06-06T21:19:36Z"]},{"key":"dc:date.issued","label":"Date","values":["2013"]},{"key":"dc:publisher","label":"Institution","values":["Wake Forest University"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10339/38565"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Exploratory cluster analysis of large data sets often implements k-means or hierarchical methods. These routines typically exhibit limitations which reduces the reliability of the results. Both assign observations to the one component for which its Euclidean distance from the center is smallest. Furthermore, these methods force a common variance in every dimension and do not permit covariances between dimensions. A final limitation is that these methods prohibit statistical inference."]},{"key":"dc:title","label":"Title","values":["Probabilistic Finite Mixture Clustering of Genetic Expression Microarray Data"]}]}],"canonical_facts":{"dc:creator":["Higgins, Ixavier"],"dc:date.accessioned":["2013-06-06T21:19:36Z"],"dc:date.issued":["2013"],"dc:description.abstract":["Exploratory cluster analysis of large data sets often implements k-means or hierarchical methods. These routines typically exhibit limitations which reduces the reliability of the results. Both assign observations to the one component for which its Euclidean distance from the center is smallest. Furthermore, these methods force a common variance in every dimension and do not permit covariances between dimensions. A final limitation is that these methods prohibit statistical inference."],"dc:identifier.uri":["http://hdl.handle.net/10339/38565"],"dc:language.iso":["en"],"dc:publisher":["Wake Forest University"],"dc:title":["Probabilistic Finite Mixture Clustering of Genetic Expression Microarray Data"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T22:01:33Z"}