# User Portlet

Giulio Alessandrini
Discussions
I am confused by your problem setup. A single example is in -> out where in is 192 binary digits. A single modified example is in$mod -> out where in$mod is 24 integers stored as ByteArray If this is correct you can use normal to...
The easiest way right now is by using  Information[p, "DecisionTree"] // Head (* Tree *)  However, keep in mind that this tree is not acting on the input data but on the processed data. You can force the processing pipeline to be...
I personally find the JAX model compelling but I never seriously worked with it. I am courious: why you would not reccomend it's inclusion? Thanks!
The issue is with the compilation step in FunctionLayert not being able to read the downvalues for the map symbol in order to inline that in the net. This is an usupported feature at the moment.
It uses the biased estimator for the variance  x = {{1., 2., 3.}, {4., 5., 6.}, {7., 8., 9.}, {10., 11., 12.}, {13., 14., 15.}} xS01 = FeatureExtract[x, "StandardizedVector"]; xS02 = Standardize[x]; xS03 = Sqrt[Length[x]/(Length[x] -...
You can specify the point of origin of the axes.  Plot[Sin[x], {x, 0, 6 Pi}, AxesOrigin -> {6 Pi, 0}]  ![plot with y axis on the right side][1] [1]:...
It really depends on what you want your trainable parameters to be. For a model such as  a * Input1 * Input 2 + b * Input3 + c  you can use this network  FunctionLayer[ Function[ NetArray[]*#Input1*#Input2 +...
We have it in several places in the documentation. You can cite it from here for example: https://reference.wolfram.com/language/ref/FindClusters.html See the Cite As at the bottom of the page
This is not supported at the moment but it's on our todo list.
You have to pay attention to spaces  Select[NetExtract[lm, {"Output", "Labels"}], StringContainsQ["hitman", IgnoreCase -> True]] (* {" Whitman", " Hitman"} *)  The vocabulary token is " Hitman" with capital H and a space at the...