I need to use a Multi Layer Perceptron Network in order to perform some non-linear regression. Any ideas if it's possible to perform a task like that and how? Which activation function should be used for that purpose?
thanks!
2026-03-26 01:28:37.1774488517
Is a traditional Multi Layer Perceptron Network capable of non-linear regression? Which activation function should be used for that purpose?
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A multi-layer perceptron can be used for nonlinear regression. The standard backpropagation algorithm is the most common training method, and common activation functions for the hidden layer are the hyperbolic tangent and logistic function. The output neurons do not need a nonlinear activation function, you can just use linear output neurons. The universal approximation theorem for neural networks then states that you can approximate continuous functions arbitrarily well by increasing the number of hidden neurons.