Equal Width Binning
Equal Width Binning is a data preprocessing technique used in data analysis to transform continuous numerical variables into categorical variables. It involves dividing a continuous variable into a pre-defined number of equal width bins or intervals. The range of the variable is divided into intervals of equal size, and each observation is assigned to a specific interval based on its value. This technique is useful for reducing the impact of outliers and for simplifying the data analysis process. It is commonly used in data mining, machine learning, and statistical analysis.
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