Data mining via SAS Enterprise Miner

[Stewartli]

Hi guys, 

I try to develop regression models and neural networks and compare their results. Finally, both models were developed based on a particular set of input variables and hyperparameters and model comparison was used to assess them. Although a lot of theories and techniques were applied, I feel I never get to the bottom, not even close to it. Does anyone have the same feeling? How do you deal with it?

Thank you. 

Stewart

[Reeza · Accepted solution]

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@Stewartli wrote:

I feel I never get to the bottom, not even close to it. Does anyone have the same feeling? How do you deal with it?

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Hi ladies, 

Depends on what you mean by that. 

If you're referring to how you're model seems inadequate and you feel you can keep going, then definitely. At some point you have to say good enough and move on. 

If you're referring to how you feel like you don't understand what's going on, that's understandable. I understood all the math a decade ago, much less so now, but I'm much better at building my feature sets and actually making a practical impact with the models these days. A simple model I can explain with 85% accuracy may be much better than a neural network with an accuracy (modelled) of 90%.  Especially if it's going to be used in a public manner (I work for gov). 

If I've misinterpreted your question, let me know. 

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@Stewartli wrote:

Hi guys, 

I try to develop regression models and neural networks and compare their results. Finally, both models were developed based on a particular set of input variables and hyperparameters and model comparison was used to assess them. Although a lot of theories and techniques were applied, I feel I never get to the bottom, not even close to it. Does anyone have the same feeling? How do you deal with it?

Thank you. 

Stewart

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