Modeling and evaluation

The package that we will use is neuralnet. The function in neuralnet will call for the use of a formula as we used elsewhere, such as y~x1+x2+x3+x4, data = df. In the past, we used y~. to specify all the other variables in the data as inputs. However, neuralnet does not accommodate this at the time of writing this. The way around this limitation is to use the as.formula() function. After first creating an object of the variable names, we will use this as an input in order to paste the variables properly on the right side of the equation:

> n = names(shuttleTrain)

> n
 [1] "stability.xstab" "error.MM"        "error.SS"       
 [4] "error.XL"        "sign.pp"         "wind.tail"      
 [7] "magn.Medium"     "magn.Out"        "magn.Strong"    
[10] "vis.yes"         "use"            

> form ...

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