R help - Apr 2003 - SVM module: scaling data applied to new test set without using SVM again

Hello!

We are new in  using R.  We use the SVM module from the library
''e1071''
for training. 

Problem formulation:

a classification has been performed using SVM module (linear kernel). 
Later, a new data set (test set) comparable to the training data shall be 
scaled in the same way  as the training set (using the same scaling 
parameter set, but without using the SVM again to save time). We found the 
scaling matrices, but we do not know, how to apply them. 

How must the scaling parameter matrices (scaled:center and scaled:scale) 
be applied to the test data set to receive the same scaling as it would 
have been done by the SVM module?

Thanx very much in advance!
	[[alternate HTML version deleted]]

seidel at micro-biolytics.com wrote:
> 
> Hello!
> 
> We are new in  using R.  We use the SVM module from the library
'e1071'
> for training.
> 
> Problem formulation:
> 
> a classification has been performed using SVM module (linear kernel).
> Later, a new data set (test set) comparable to the training data shall be
> scaled in the same way  as the training set (using the same scaling
> parameter set, but without using the SVM again to save time). We found the
> scaling matrices, but we do not know, how to apply them.
[note: in the `x.scale' element of the fitted model]
> 
> How must the scaling parameter matrices (scaled:center and scaled:scale)
> be applied to the test data set to receive the same scaling as it would
> have been done by the SVM module?
the function `scale' has two parameters: `center' and `scale'.
So, you could do sth. like:

scale(newdata, 
      center = model$x.scale$"scaled:center", 
      scale = model$x.scale$"scaled:scale")

best,
	
David
> 
> Thanx very much in advance!
>         [[alternate HTML version deleted]]
> 
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