I am wondering if I can use neural networks to find features importances in similar manner as it can be done for random forests or decision trees and if so, how to do it?
I would like to use it on tabular time series data (not images). The reason why I want to find importances on neural networks not on decision trees is that NNs are more complicated algorithms so using NNs might point out some correlations that are not seen by simple algorithms and I need to know what features are found to be more useful with that complicated correlations.
I am not sure if I made it clear enough, please let me know if I have to explain something more.
olden()
function fromNeuralNetTools
. Please take a look at this example found online: blogs2.datall-analyse.nl/2016/02/19/… $\endgroup$