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I'm using the "brnn" package (Bayesian Regularized Neural Networks), in particular I run the train() function from caret package. My data are stored in a data.frame object and I run the caret function using the "formula" way y ~. (in the "point" there are seven variables that we can call here x1,x2,x3....x7) I would like to understand how to write the formula of brnn method using the values obtained from R. I obtained the following results.

   - MY_results$finalModel$theta 

   - MY_results$finalModel$alpha

   - MY_results$finalModel$beta

   - MY_results$finalModel$gamma

   - MY_results$finalModel$Ed

   - MY_results$finalModel$Ew

   - MY_results$finalModel$F_history

   - MY_results$finalModel$reason

   - MY_results$finalModel$epoch

   - MY_results$finalModel$neurons

   - MY_results$finalModel$p

   - MY_results$finalModel$n

   - MY_results$finalModel$npar

   - MY_results$finalModel$x_normalized

   - MY_results$finalModel$x_base

   - MY_results$finalModel$x_spread

   - MY_results$finalModel$y_base

   - MY_results$finalModel$y_spread

   - MY_results$finalModel$y

   - MY_results$finalModel$normalize

   - MY_results$finalModel$call

   - MY_results$finalModel$xNames

   - MY_results$finalModel$problemType

   - MY_results$finalModel$tuneValue

   - MY_results$finalModel$obsLevels

   - MY_results$finalModel$param

I tried to reproduce the brnn formula described in https://cran.r-project.org/web/packages/brnn/brnn.pdf, but I'm not sure how to consider variables x1,x2....x7.

Thank you in advance for any kind of suggestions.

Elisa

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