Backpropagating quasi-randomized neural networks
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The FiniteDiffRegressor – implemented in Python package tisthemachinelearner – blends a finite difference-based training algorithm for (quasi-)randomized artificial neural network models’ weights with any supervised Machine Learning regression model.
More details about the implementation can be found in this technical note:
https://www.researchgate.net/publication/392923564_Backpropagating_quasi-randomized_neural_networks
On GitHub:
https://github.com/Techtonique/tisthemachinelearner
And here is a link to the notebook containing examples of use of FiniteDiffRegressor:
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