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Here\[CloseCurlyQuote]s the present situation of the experimental global \
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For the SNN to be applied, we need to normalize this the way the training \
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Let\[CloseCurlyQuote]s create the best ensemble-net for this data-set and \
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But this is just the central value-set. Let\[CloseCurlyQuote]s extract a \
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Let\[CloseCurlyQuote]s check how these are distributed in the R(D) - R(D*) \
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As explained in the paper, we can apply the net on all of these points, \
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\[CloseCurlyQuote]s do this for a new sample of 1000 points. This is done by:\
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This is easily repeatable for the other two data-sets with 5 and 13 \
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The order of the observables for the different data-sets are:\
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