A performance bound of the multi-output extreme learning machine classifier
Author:
Funder
The Study of the Hail Potential Forecasting Techniques Based on Data Mining in Tianjin
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,General Computer Science
Link
http://link.springer.com/content/pdf/10.1007/s12293-018-0270-9.pdf
Reference31 articles.
1. Huang GB, Wang DH, Lan Y (2011) Extreme learning machines: a survey. Int J Mach Learn Cybern 2(2):107–122
2. Huang G, Huang GB, Song S, You K (2015) Trends in extreme learning machines: a review. Neural Netw 61(C):32–48
3. Cao J, Zhang K, Luo M, Yin C, Lai X (2016) Extreme learning machine and adaptive sparse representation for image classification. Neural Netw 81(C):91
4. Kim J, Kim J, Jang GJ, Lee M (2017) Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection. Neural Netw 87:109–121
5. Liu H, Li F, Xu X, Sun F (2018) Active object recognition using hierarchical local-receptive-field-based extreme learning machine. Memet Comput 10(2):233–241
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