Data Binning
Data binning is a data pre-processing technique used to reduce the effects of minor observation errors. It involves grouping a set of continuous or numerical data points into a smaller number of 'bins' or intervals. This is done by dividing the range of the data into equal width intervals and then mapping each data point to its corresponding interval. Binning can also be done by dividing the data into equal frequency intervals, where each bin contains approximately the same number of data points. Data binning is useful in data analysis as it can help to simplify the data and make it easier to visualize. It can also be used to smooth out noisy data and identify trends or patterns that may not be apparent in the raw data.
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