Regularized based implicit Lagrangian twin extreme learning machine in primal for pattern classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s13042-020-01235-y.pdf
Reference69 articles.
1. Aslan MF, Sabanci A, Durdu A (2017) Different Wheat Species Classifier Application of ANN and ELM. J Multidiscipl Eng Sci Technol 4(9):8194–8198
2. Balasundaram S, Gupta D (2016) On optimization based extreme learning machine in primal for regression and classification by functional iterative method. Int J Mach Learn Cybern 7(5):707–728
3. Balasundaram S, Gupta D, Kapil S (2014) 1-Norm extreme learning machine for regression and multiclass classification using Newton method. Neurocomputing 128:4–14
4. Balasundaram S, Gupta D, Prasad SC (2017) A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization. Appl Intell 46:124–134. https://doi.org/10.1007/s10489-016-0809-8
5. Balasundaram S, Tanveer M (2013) On Lagrangian twin support vector regression. Neural Comput Appl 22(1):257–267
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