Data binning

Data binning is a data pre-processing technique used when small instrumental shifts in the spectral dimension from for example MS or NMR experiments will be falsely interpreted as representing different components when a collection of data profiles is subjected to pattern recognition analysis. A straightforward way to cope with this problem is by using binning techniques in which the spectrum is reduced in resolution to a sufficient degree to ensure that a given peak remains its bin despite small spectral shifts between analyses. For example, in NMR the chemical shift axis may be dscretized and coarsely binned, and in MS the spectral accuracies may be rounded to integer atomic mass unit values.