binning - Fitting bins described by proportions between them to a dataset -


i have given array of floats want use bins quantize given dataset with. interested in, however, best value x exists, when multiplied each of these bins proportions builds bins best fit dataset distribution.

for example, bin array of:

{0.25, 0.5, 1.0, 1.5, 2.0}

and dataset comprised of values:

{12051, 6003, 24047, 3021, 17983}

would give me actual appropriate bins best fit dataset close to:

{3000.0, 6000.0, 12000.0, 18000.0, 24000.0}

which mean x approximately 12000.0

12000.0 * {0.25, 0.5, 1.0, 1.5, 2.0} = {3000.0, 6000.0, 12000.0, 18000.0, 24000.0}

both bin array , dataset known, x needs calculated , of course, want work number of bins , dataset size. method or technique can use achieve this?


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