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Data binning

Data binning (also called Discrete binning or bucketing) is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall in a given small interval, a bin, are replaced by a value representative of that interval, often the central value. It is a form of quantization. Data binning (also called Discrete binning or bucketing) is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall in a given small interval, a bin, are replaced by a value representative of that interval, often the central value. It is a form of quantization. Statistical data binning is a way to group a number of more or less continuous values into a smaller number of 'bins'. For example, if you have data about a group of people, you might want to arrange their ages into a smaller number of age intervals (for example, grouping every five years together). It can also be used in multivariate statistics, binning in several dimensions at once. In the context of image processing, binning is the procedure of combining a cluster of pixels into a single pixel. As such, in 2x2 binning, an array of 4 pixels becomes a single larger pixel, reducing the overall number of pixels.

[ "Algorithm", "Statistics", "Machine learning", "Data mining", "Artificial intelligence" ]
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