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R: Pre-processing package Caret ()

I'm new to data modeling and R, I wonder if anyone can give me some advice.

I am using R to replicate a model I created in the SPSS module and then try to improve it. I am currently building a basic linear model using the caret package.

I used preProcess () to scale and center my numeric fields, including the numeric variable that the model predicts.

preProcValues <- preProcess(Data_Numeric, method = c("center", "scale"))
Data_PreProc <- predict(preProcValues, Data_Numeric)

When I create the model I find that this preprocessing results in a more accurate model, however I am not sure how to take the scaled and centered result and get the "result". The model is being used as a pricing tool, so I need to expand and center it if that makes sense?

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For centering

, the sample mean is subtracted, and the centered values ​​are divided by the standard deviation for scaling

.

It will be easily restored from the following relationship.



  • data
  • centered = data - average (data)
  • scaled = centered / sd (data)
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