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I have a sample with around 2000 observations and 10 variables which im using for classification. I plan on classifying the data with a neural net, but before doing so im using Weka's attribute selection feature to select the best combination of attributes (based on accuracy) for the model via subset evaluation.

The thing is, the attribute selection in Weka only results in the absolute best model found, and i'd like to generate a list with at least the five best ones in order of accuracy, similar to how the bestglm package in R does for generalized linear models by ranking them in order of AIC, BIC, etc.

Is there a method using R or Weka that does the same for neural nets?

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How about trying "geneticSearch" option, in In method selection as shown.

Though I m not sure this is what you are looking for :( enter image description here

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  • $\begingroup$ That might work, i'll look into the geneticSearch method to make sure. $\endgroup$ – pdebem Sep 22 '16 at 17:05

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