# brnn r package (Bayesian Regularization for Feed-Forward Neural Networks)

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