{"main_file_link":[{"url":"https://www.th-owl.de/init/uploads/tx_initdb/00800426_01.pdf","open_access":"1"}],"status":"public","keyword":["Fuzzy Logic","Probability Theory","Fuzzy-Pattern-Classification","Machine Learning","Artificial Intelligence","Pattern Recognition"],"author":[{"last_name":"Mönks","first_name":"Uwe","id":"1825","full_name":"Mönks, Uwe"},{"id":"1804","orcid":"0000-0002-3325-7887","full_name":"Lohweg, Volker","last_name":"Lohweg","first_name":"Volker"},{"full_name":"Petker, Denis","last_name":"Petker","first_name":"Denis"}],"publisher":"28 Jun 2010 - 02 July 2010, Dortmund, Germany","type":"conference","citation":{"mla":"Mönks, Uwe, et al. “Fuzzy-Pattern-Classifier Training with Small Data Sets.” IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.","ieee":"U. Mönks, V. Lohweg, and 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, 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.","ufg":"Mönks, Uwe et. al. (2010): Fuzzy-Pattern-Classifier Training with Small Data Sets, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems.","apa":"Mönks, U., Lohweg, V., & Petker, D. (2010). 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.","bjps":"Mönks U, Lohweg V and Petker D (2010) Fuzzy-Pattern-Classifier Training with Small Data Sets. IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany.","chicago":"Mönks, Uwe, Volker Lohweg, and Denis 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.","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.","chicago-de":"Mönks, Uwe, Volker Lohweg und Denis Petker. 2010. 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.","din1505-2-1":"Mönks, Uwe ; Lohweg, Volker ; Petker, Denis: 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: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany; 2010.","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."},"department":[{"_id":"DEP5023"}],"language":[{"iso":"eng"}],"title":"Fuzzy-Pattern-Classifier Training with Small Data Sets","date_updated":"2023-03-15T13:49:38Z","user_id":"45673","date_created":"2019-12-02T08:15:18Z","year":2010,"_id":"2087","oa":"1","abstract":[{"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.","lang":"eng"}],"publication_status":"published","publication":"IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems"}