An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem
المؤلفون المشاركون
Bian, Jing
Peng, Xin-guang
Wang, Ying
Zhang, Hai
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-06-20
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
In the era of big data, feature selection is an essential process in machine learning.
Although the class imbalance problem has recently attracted a great deal of attention, little effort has been undertaken to develop feature selection techniques.
In addition, most applications involving feature selection focus on classification accuracy but not cost, although costs are important.
To cope with imbalance problems, we developed a cost-sensitive feature selection algorithm that adds the cost-based evaluation function of a filter feature selection using a chaos genetic algorithm, referred to as CSFSG.
The evaluation function considers both feature-acquiring costs (test costs) and misclassification costs in the field of network security, thereby weakening the influence of many instances from the majority of classes in large-scale datasets.
The CSFSG algorithm reduces the total cost of feature selection and trades off both factors.
The behavior of the CSFSG algorithm is tested on a large-scale dataset of network security, using two kinds of classifiers: C4.5 and k -nearest neighbor (KNN).
The results of the experimental research show that the approach is efficient and able to effectively improve classification accuracy and to decrease classification time.
In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Bian, Jing& Peng, Xin-guang& Wang, Ying& Zhang, Hai. 2016. An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112759
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Bian, Jing…[et al.]. An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem. Mathematical Problems in Engineering No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1112759
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Bian, Jing& Peng, Xin-guang& Wang, Ying& Zhang, Hai. An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112759
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1112759
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