"Multi Label Regression with neuronal network"
Hi,
I am trying (for quite some time now, so please help;) to build a neuronal network with
several input layers (attributes) and several outputlayers (labels) for a regression. All variables are numerical.
I want just one NN giving me all numerical labels, not just one label in several models.
As obvious as this problem seems to me, I couldn find anything suitable so far here.
My principal Idea, at first, was to build one model per label and then stack them together in one model.
Below the code of a model that loops through the labels and creates seperate models.
是what Im proposing here even possible with RM?
I really would appreciate your help.
Cheers
Julian
< portSpacing端口= " source_example set" spacing="0"/>
< portSpacing端口= " sink_result 3”间隔= " 0 " / >
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Answers
Has anyone suceeded in building a Neuronal Net with multiple numerical labels so far?
Cant be that Iam the only one trying this. Please, just tell me if i dont get it or if it is just not possible.
Julian
You can do Vector Linear Regression. But this is more like a perceptron.
To what purpose you need a neural network with multiple outputs?
Are you capable of coding a neural network yourself? It may turn out to be surprisingly easy.
Best regards,
Wessel