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In
statistics Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of ...
and
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
, discretization refers to the process of converting or partitioning continuous
attributes Attribute may refer to: * Attribute (philosophy), an extrinsic property of an object * Attribute (research), a characteristic of an object * Grammatical modifier, in natural languages * Attribute (computing), a specification that defines a proper ...
,
features Feature may refer to: Computing * Feature (CAD), could be a hole, pocket, or notch * Feature (computer vision), could be an edge, corner or blob * Feature (software design) is an intentional distinguishing characteristic of a software item ...
or variables to discretized or
nominal Nominal may refer to: Linguistics and grammar * Nominal (linguistics), one of the parts of speech * Nominal, the adjectival form of "noun", as in "nominal agreement" (= "noun agreement") * Nominal sentence, a sentence without a finite verb * Nou ...
attributes/features/variables/
intervals Interval may refer to: Mathematics and physics * Interval (mathematics), a range of numbers ** Partially ordered set#Intervals, its generalization from numbers to arbitrary partially ordered sets * A statistical level of measurement * Interval est ...
. This can be useful when creating probability mass functions – formally, in
density estimation In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought o ...
. It is a form of
discretization In applied mathematics, discretization is the process of transferring continuous functions, models, variables, and equations into discrete counterparts. This process is usually carried out as a first step toward making them suitable for numerical ...
in general and also of binning, as in making a
histogram A histogram is an approximate representation of the distribution of numerical data. The term was first introduced by Karl Pearson. To construct a histogram, the first step is to " bin" (or "bucket") the range of values—that is, divide the ent ...
. Whenever
continuous Continuity or continuous may refer to: Mathematics * Continuity (mathematics), the opposing concept to discreteness; common examples include ** Continuous probability distribution or random variable in probability and statistics ** Continuous ...
data is discretized, there is always some amount of
discretization error In numerical analysis, computational physics, and simulation, discretization error is the error resulting from the fact that a function of a continuous variable is represented in the computer by a finite number of evaluations, for example, on a l ...
. The goal is to reduce the amount to a level considered
negligible {{Short pages monitor