BD-ELM: A Regularized Extreme Learning Machine Using Biased DropConnect and Biased Dropout
المؤلفون المشاركون
Song, Yafei
Wang, Xiaodan
Lai, Jie
Li, Rui
Lei, Lei
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-29
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص EN
In order to prevent the overfitting and improve the generalization performance of Extreme Learning Machine (ELM), a new regularization method, Biased DropConnect, and a new regularized ELM using the Biased DropConnect and Biased Dropout (BD-ELM) are both proposed in this paper.
Like the Biased Dropout to hidden nodes, the Biased DropConnect can utilize the difference of connection weights to keep more information of network after dropping.
The regular Dropout and DropConnect set the connection weights and output of the hidden layer to 0 with a single fixed probability.
But the Biased DropConnect and Biased Dropout divide the connection weights and hidden nodes into high and low groups by threshold, and set different groups to 0 with different probabilities.
Connection weights with high value and hidden nodes with a high-activated value, which make more contribution to network performance, will be kept by a lower drop probability, while the weights and hidden nodes with a low value will be given a higher drop probability to keep the drop probability of the whole network to a fixed constant.
Using Biased DropConnect and Biased Dropout regularization, in BD-ELM, the sparsity of parameters is enhanced and the structural complexity is reduced.
Experiments on various benchmark datasets show that Biased DropConnect and Biased Dropout can effectively address the overfitting, and BD-ELM can provide higher classification accuracy than ELM, R-ELM, and Drop-ELM.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lai, Jie& Wang, Xiaodan& Li, Rui& Song, Yafei& Lei, Lei. 2020. BD-ELM: A Regularized Extreme Learning Machine Using Biased DropConnect and Biased Dropout. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1194528
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lai, Jie…[et al.]. BD-ELM: A Regularized Extreme Learning Machine Using Biased DropConnect and Biased Dropout. Mathematical Problems in Engineering No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1194528
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lai, Jie& Wang, Xiaodan& Li, Rui& Song, Yafei& Lei, Lei. BD-ELM: A Regularized Extreme Learning Machine Using Biased DropConnect and Biased Dropout. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1194528
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1194528
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