# Show neural net weights (Flux)
**URL:** https://discourse.julialang.org/t/show-neural-net-weights-flux/98219
**Category:** New to Julia
**Created:** [May 2, 2023, 7:29pm UTC](https://discourse.julialang.org/t/show-neural-net-weights-flux/98219 "2023-05-02T19:29:22Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@Ribeiro](https://discourse.julialang.org/u/Ribeiro)
#### Post date: [May 2, 2023, 7:29pm UTC](https://discourse.julialang.org/t/show-neural-net-weights-flux/98219/1 "2023-05-02T19:29:22Z")
Hello, folks.
I built a simple classification neural net in `Flux` (6 inputs in a `Dense` layer, a `BatchNorm` hidden layer with 13 neurons, another `Dense` 13 neuron output layer) and I was looking for some way to correlate the outputs and inputs. For instance, based on the weights assigned by `Flux`, what are the input neurons that are most important?
For instance: let’s say one of the outputs is “cat” and one is “mouse” and the inputs are height, number of legs, etc. By looking at the weights, maybe I can figure out that the most important distinguishing factor between a “cat” and a “mouse” is the height. So I’m looking for an elegant way to plot that.
I noticed that for the `Dense` layers I can use `layer.weight`, but I’m not sure for the `BatchNorm` layer. Also, the weight matrices are large, so I’m looking for a clever way to look at all the weights easily for a given input. Maybe a graph where the lines connecting the neurons are colored by the weights?
Thanks a lot!
---
### Author:  [@gdalle](https://discourse.julialang.org/u/gdalle)
#### Post date: [May 2, 2023, 9:31pm UTC](https://discourse.julialang.org/t/show-neural-net-weights-flux/98219/2 "2023-05-02T21:31:38Z")
Hi @Ribeiro!
Not sure I can help a lot but for what it’s worth, before being a Flux.jl question, it’s a math research question. A keyword you might use is “feature importance”. So I’m not sure you’ll find a lot of things ready to use, but there are some packages that can do it:
- [ML feature importance in julia](https://discourse.julialang.org/t/ml-feature-importance-in-julia/17196)
- [Feature importance / model inspection · Issue #403 · alan-turing-institute/MLJ.jl · GitHub](https://github.com/alan-turing-institute/MLJ.jl/issues/403)
---
### Author:  [@Ribeiro](https://discourse.julialang.org/u/Ribeiro)
#### Post date: [May 3, 2023, 8:05am UTC](https://discourse.julialang.org/t/show-neural-net-weights-flux/98219/3 "2023-05-03T08:05:38Z")
Thank you @gdalle . I did not know the term “feature importance”, so that alone is already helpful!
It seems `Duff.jl` might be able to do what I want, maybe `ShapML.jl` too (though the documentation of the latter doesn’t have any `Flux` examples, it says it is model agnostic). There’s also `KoalaTrees.jl`, but that seems very outdated in terms of Julia versions.
If anyone has a working example with a `Flux` NN, that’d be much appreciated. Otherwise, I’ll dig into these two.
Thanks again!