![](/images/graphics-bg.png)
A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification
المؤلفون المشاركون
Piao, Yongjun
Piao, Minghao
Jin, Cheng Hao
Shon, Ho Sun
Chung, Ji-Moon
Hwang, Buhyun
Ryu, Keun Ho
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-19
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Ensemble data mining methods, also known as classifier combination, are often used to improve the performance of classification.
Various classifier combination methods such as bagging, boosting, and random forest have been devised and have received considerable attention in the past.
However, data dimensionality increases rapidly day by day.
Such a trend poses various challenges as these methods are not suitable to directly apply to high-dimensional datasets.
In this paper, we propose an ensemble method for classification of high-dimensional data, with each classifier constructed from a different set of features determined by partitioning of redundant features.
In our method, the redundancy of features is considered to divide the original feature space.
Then, each generated feature subset is trained by a support vector machine, and the results of each classifier are combined by majority voting.
The efficiency and effectiveness of our method are demonstrated through comparisons with other ensemble techniques, and the results show that our method outperforms other methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Piao, Yongjun& Piao, Minghao& Jin, Cheng Hao& Shon, Ho Sun& Chung, Ji-Moon& Hwang, Buhyun…[et al.]. 2015. A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1074219
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Piao, Yongjun…[et al.]. A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification. Mathematical Problems in Engineering No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1074219
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Piao, Yongjun& Piao, Minghao& Jin, Cheng Hao& Shon, Ho Sun& Chung, Ji-Moon& Hwang, Buhyun…[et al.]. A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1074219
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1074219
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
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
![](/images/kashef-image.png)