Dudek proposes setting the weights and biases of random hidden-layer sigmoids using local linear fits to the target function, and shows improved regression accuracy on a synthetic function and two real datasets.
I nformation Sciences 473, 73–86 (2019)
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Data-Driven Randomized Learning of Feedforward Neural Networks
Dudek proposes setting the weights and biases of random hidden-layer sigmoids using local linear fits to the target function, and shows improved regression accuracy on a synthetic function and two real datasets.