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{{see also|Machine learning terms}} | |||
==Introduction== | ==Introduction== | ||
'''Bucketing''', also referred to as '''binning''', is a [[data preprocessing]] technique in [[machine learning]] that groups [[continuous numerical data]] into [[discrete categories]] or '''buckets''' or '''bins''' based on their range of values. This can be advantageous for various reasons such as simplifying the data, eliminating [[noise]] and [[outliers]], and improving [[model]] [[accuracy]]. In this article we'll provide an overview of bucketing in machine learning including its advantages, potential drawbacks, and how it's implemented. | '''Bucketing''', also referred to as '''binning''', is a [[data preprocessing]] technique in [[machine learning]] that groups [[continuous numerical data]] into [[discrete categories]] or '''buckets''' or '''bins''' based on their range of values. This can be advantageous for various reasons such as simplifying the data, eliminating [[noise]] and [[outliers]], and improving [[model]] [[accuracy]]. In this article we'll provide an overview of bucketing in machine learning including its advantages, potential drawbacks, and how it's implemented. | ||
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==Explain Like I'm 5 (ELI5)== | ==Explain Like I'm 5 (ELI5)== | ||
Bucketing or binning is like sorting your toys into distinct boxes. Just as you might have a box for toy cars and another for dolls, bucketing occurs when a computer groups items that are similar. | Bucketing or binning is like sorting your toys into distinct boxes. Just as you might have a box for toy cars and another for dolls, bucketing occurs when a computer groups items that are similar. | ||
[[Category:Terms]] [[Category:Machine learning terms]] |