Classifying Imbalanced Data Sets by a Novel RE-Sample and Cost-Sensitive Stacked Generalization Method
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-01-23
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Learning with imbalanced data sets is considered as one of the key topics in machine learning community.
Stacking ensemble is an efficient algorithm for normal balance data sets.
However, stacking ensemble was seldom applied in imbalance data.
In this paper, we proposed a novel RE-sample and Cost-Sensitive Stacked Generalization (RECSG) method based on 2-layer learning models.
The first step is Level 0 model generalization including data preprocessing and base model training.
The second step is Level 1 model generalization involving cost-sensitive classifier and logistic regression algorithm.
In the learning phase, preprocessing techniques can be embedded in imbalance data learning methods.
In the cost-sensitive algorithm, cost matrix is combined with both data characters and algorithms.
In the RECSG method, ensemble algorithm is combined with imbalance data techniques.
According to the experiment results obtained with 17 public imbalanced data sets, as indicated by various evaluation metrics (AUC, GeoMean, and AGeoMean), the proposed method showed the better classification performances than other ensemble and single algorithms.
The proposed method is especially more efficient when the performance of base classifier is low.
All these demonstrated that the proposed method could be applied in the class imbalance problem.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yan, Jianhong& Han, Suqing. 2018. Classifying Imbalanced Data Sets by a Novel RE-Sample and Cost-Sensitive Stacked Generalization Method. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1207792
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yan, Jianhong& Han, Suqing. Classifying Imbalanced Data Sets by a Novel RE-Sample and Cost-Sensitive Stacked Generalization Method. Mathematical Problems in Engineering No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1207792
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yan, Jianhong& Han, Suqing. Classifying Imbalanced Data Sets by a Novel RE-Sample and Cost-Sensitive Stacked Generalization Method. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1207792
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1207792
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