Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier
المؤلفون المشاركون
Moreira, Leandro Juvêncio
Silva, Leandro A.
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-07-25
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
The k nearest neighbor is one of the most important and simple procedures for data classification task.
The kNN, as it is called, requires only two parameters: the number of k and a similarity measure.
However, the algorithm has some weaknesses that make it impossible to be used in real problems.
Since the algorithm has no model, an exhaustive comparison of the object in classification analysis and all training dataset is necessary.
Another weakness is the optimal choice of k parameter when the object analyzed is in an overlap region.
To mitigate theses negative aspects, in this work, a hybrid algorithm is proposed which uses the Self-Organizing Maps (SOM) artificial neural network and a classifier that uses similarity measure based on information.
Since SOM has the properties of vector quantization, it is used as a Prototype Generation approach to select a reduced training dataset for the classification approach based on the nearest neighbor rule with informativeness measure, named iNN.
The SOMiNN combination was exhaustively experimented and the results show that the proposed approach presents important accuracy in databases where the border region does not have the object classes well defined.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Moreira, Leandro Juvêncio& Silva, Leandro A.. 2017. Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1140950
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Moreira, Leandro Juvêncio& Silva, Leandro A.. Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1140950
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Moreira, Leandro Juvêncio& Silva, Leandro A.. Prototype Generation Using Self-Organizing Maps for Informativeness-Based Classifier. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1140950
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1140950
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر