View Single Post
  #2  
Old 11-01-2013, 12:22 PM
magdon's Avatar
magdon magdon is offline
RPI
 
Join Date: Aug 2009
Location: Troy, NY, USA.
Posts: 595
Default Re: Input Normalization

Feature normalization (as in the example of data snooping in financial trading in chapter 5) is based on the data itself. Similarly in the assignment, the feature normalization is based on the data.

Quote:
Originally Posted by Sweater Monkey View Post
I could use some clarification on the 9th homework assignment.

In normalizing the features I would assume that it is with respect to the bounds on the feature's possible values rather than on the data itself?

For example, the minimum pixel intensity is for the digit data is -1 and the maximum is +1 therefore, using average pixel intensity as a feature, the min and max average pixel intensities that are possible are -1 and +1 (if all pixels were white or all pixels were black for a given data point). So in this case I am under the assumption that the feature doesn't need any shift or scale normalization since the min and max values are already within the [-1,1] bound regardless of the data. Is this correct?
__________________
Have faith in probability
Reply With Quote