Feature Selection and Overlapping Clustering-Based Multilabel Classification Model
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-01-04
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Multilabel classification (MLC) learning, which is widely applied in real-world applications, is a very important problem in machine learning.
Some studies show that a clustering-based MLC framework performs effectively compared to a nonclustering framework.
In this paper, we explore the clustering-based MLC problem.
Multilabel feature selection also plays an important role in classification learning because many redundant and irrelevant features can degrade performance and a good feature selection algorithm can reduce computational complexity and improve classification accuracy.
In this study, we consider feature dependence and feature interaction simultaneously, and we propose a multilabel feature selection algorithm as a preprocessing stage before MLC.
Typically, existing cluster-based MLC frameworks employ a hard cluster method.
In practice, the instances of multilabel datasets are distinguished in a single cluster by such frameworks; however, the overlapping nature of multilabel instances is such that, in real-life applications, instances may not belong to only a single class.
Therefore, we propose a MLC model that combines feature selection with an overlapping clustering algorithm.
Experimental results demonstrate that various clustering algorithms show different performance for MLC, and the proposed overlapping clustering-based MLC model may be more suitable.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Peng, Liwen& Liu, Yongguo. 2018. Feature Selection and Overlapping Clustering-Based Multilabel Classification Model. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1206478
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Peng, Liwen& Liu, Yongguo. Feature Selection and Overlapping Clustering-Based Multilabel Classification Model. Mathematical Problems in Engineering No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1206478
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Peng, Liwen& Liu, Yongguo. Feature Selection and Overlapping Clustering-Based Multilabel Classification Model. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1206478
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1206478
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