Hi all.
I have some questions on the interpretation of neural network results. The contect is classification , particularly the creation of a retention models where the outcome of the model is a classification of records that are likely to abandon the company. Compared to the decision tree, that has a graphical output where you may, looking at the different branches and trees, have a look at the details of the model, he neural network interpretation seems harder.
Are there any specific nodes or examples that may help in the interpretation of the output table of a neural network model?
Thanks!
G