A Cost-Sensitive Sparse Representation Based Classification for Class-Imbalance Problem
المؤلفون المشاركون
Liu, Zhenbing
Gao, Chunyang
Yang, Huihua
He, Qijia
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-12-22
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Sparse representation has been successfully used in pattern recognition and machine learning.
However, most existing sparse representation based classification (SRC) methods are to achieve the highest classification accuracy, assuming the same losses for different misclassifications.
This assumption, however, may not hold in many practical applications as different types of misclassification could lead to different losses.
In real-world application, much data sets are imbalanced of the class distribution.
To address these problems, we propose a cost-sensitive sparse representation based classification (CSSRC) for class-imbalance problem method by using probabilistic modeling.
Unlike traditional SRC methods, we predict the class label of test samples by minimizing the misclassification losses, which are obtained via computing the posterior probabilities.
Experimental results on the UCI databases validate the efficacy of the proposed approach on average misclassification cost, positive class misclassification rate, and negative class misclassification rate.
In addition, we sampled test samples and training samples with different imbalance ratio and use F -measure, G -mean, classification accuracy, and running time to evaluate the performance of the proposed method.
The experiments show that our proposed method performs competitively compared to SRC, CSSVM, and CS4VM.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Zhenbing& Gao, Chunyang& Yang, Huihua& He, Qijia. 2016. A Cost-Sensitive Sparse Representation Based Classification for Class-Imbalance Problem. Scientific Programming،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118377
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Zhenbing…[et al.]. A Cost-Sensitive Sparse Representation Based Classification for Class-Imbalance Problem. Scientific Programming No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1118377
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Zhenbing& Gao, Chunyang& Yang, Huihua& He, Qijia. A Cost-Sensitive Sparse Representation Based Classification for Class-Imbalance Problem. Scientific Programming. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118377
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1118377
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