­
­
­
­

Inventi Impact: Artificial Intelligence

Articles

  • Inventi:eai/23494/17
    Improving Classification Performance through an Advanced Ensemble Based Heterogeneous\nExtreme Learning Machines
    01-Jan-1970 Research 2017 : October - December
    Adnan O M Abuassba, Dezheng Zhang, Xiong Luo, Ahmad Shaheryar, Hazrat Ali

    Extreme Learning Machine (ELM) is a fast-learning algorithm for a single-hidden layer feedforward neural network (SLFN). It\noften has good generalization performance. However, there are chances that it might overfit the training data due to having more\nhidden nodes than needed. To address the generalization performance, we use a heterogeneous ensemble approach. We propose\nan Advanced ELM Ensemble (AELME) for classification, which includes Regularized-ELM,

    How to Cite this Article
    CC Compliant Citation: Adnan O. M. Abuassba, Dezheng Zhang,\nXiong Luo, Ahmad Shaheryar, and Hazrat Ali, â??Improving\nClassification Performance through an Advanced Ensemble\nBased Heterogeneous Extreme Learning Machines,â?\nComputational Intelligence and Neuroscience, vol. 2017, Article\nID 3405463, 11 pages, 2017. doi:10.1155/2017/3405463,\nhttp://creativecommons.org/licenses/by/4.0/.
    Download Full Text