Mexican hat wavelet kernel elm for multiclass classification

HIGHLIGHTS

• who: Jie Wang and collaborators from the School of Electrical Engineering, Zhengzhou University, Zhengzhou, China have published the research: Mexican Hat Wavelet Kernel ELM for Multiclass Classification, in the Journal: Computational Intelligence and Neuroscience of 21/02/2017
• what: In this model, input weights and hidden layer biases are initialized randomly, and output weights are obtained by using the Moore-Penrose generalized inverse of the hidden layer output matrix. The authors propose a Mexican Hat wavelet kernel ELM (MHW-KELM) classifier, which effectively solves the problems in the conventional classifier.
• how: The data . . .
  

   

  

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