{"publication":"IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems","department":[{"_id":"DEP5023"}],"citation":{"ieee":"U. Mönks, V. Lohweg, and D. Petker, “Fuzzy-Pattern-Classifier Training with Small Data Sets,” in <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>, 2010.","short":"U. Mönks, V. Lohweg, D. Petker, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.","bjps":"<b>Mönks U, Lohweg V and Petker D</b> (2010) Fuzzy-Pattern-Classifier Training with Small Data Sets. <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>. 28 Jun 2010 - 02 July 2010, Dortmund, Germany.","ufg":"<b>Mönks, Uwe et. al. (2010)</b>: Fuzzy-Pattern-Classifier Training with Small Data Sets, in: <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>.","van":"Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany; 2010.","havard":"U. Mönks, V. Lohweg, D. Petker, Fuzzy-Pattern-Classifier Training with Small Data Sets, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.","ama":"Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>. 28 Jun 2010 - 02 July 2010, Dortmund, Germany; 2010.","apa":"Mönks, U., Lohweg, V., &#38; Petker, D. (2010). Fuzzy-Pattern-Classifier Training with Small Data Sets. In <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>. 28 Jun 2010 - 02 July 2010, Dortmund, Germany.","mla":"Mönks, Uwe, et al. “Fuzzy-Pattern-Classifier Training with Small Data Sets.” <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.","chicago-de":"Mönks, Uwe, Volker Lohweg und Denis Petker. 2010. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>. 28 Jun 2010 - 02 July 2010, Dortmund, Germany.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Mönks, Uwe</span> ; <span style=\"font-variant:small-caps;\">Lohweg, Volker</span> ; <span style=\"font-variant:small-caps;\">Petker, Denis</span>: Fuzzy-Pattern-Classifier Training with Small Data Sets. In: <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i> : 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010","chicago":"Mönks, Uwe, Volker Lohweg, and Denis Petker. “Fuzzy-Pattern-Classifier Training with Small Data Sets.” In <i>IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems</i>. 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010."},"user_id":"45673","title":"Fuzzy-Pattern-Classifier Training with Small Data Sets","main_file_link":[{"url":"https://www.th-owl.de/init/uploads/tx_initdb/00800426_01.pdf","open_access":"1"}],"status":"public","type":"conference","abstract":[{"lang":"eng","text":"It is likely in real-world applications that only little data isavailable for training a knowledge-based system. We present a method forautomatically training the knowledge-representing membership functionsof a Fuzzy-Pattern-Classification system that works also when only littledata is available and the universal set is described insufficiently. Actually,this paper presents how the Modified-Fuzzy-Pattern-Classifier’s member-ship functions are trained using probability distribution functions."}],"_id":"2087","publication_status":"published","oa":"1","author":[{"first_name":"Uwe","full_name":"Mönks, Uwe","last_name":"Mönks","id":"1825"},{"id":"1804","full_name":"Lohweg, Volker","last_name":"Lohweg","first_name":"Volker","orcid":"0000-0002-3325-7887"},{"full_name":"Petker, Denis","last_name":"Petker","first_name":"Denis"}],"year":2010,"date_updated":"2023-03-15T13:49:38Z","language":[{"iso":"eng"}],"publisher":"28 Jun 2010 - 02 July 2010, Dortmund, Germany","keyword":["Fuzzy Logic","Probability Theory","Fuzzy-Pattern-Classification","Machine Learning","Artificial Intelligence","Pattern Recognition"],"date_created":"2019-12-02T08:15:18Z"}