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In general, a function approximation problem asks us to select a function among a well-defined class that closely matches ("approximates") a target function in a task-specific way. The need for function approximations arises in many branches of applied mathematics, and computer science in particular, such as predicting the growth of microbes in microbiology. Function approximations are used where theoretical models are unavailable or hard to compute. One can distinguish two major classes of function approximation problems:

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rdfs:label	Function approximation (en)
rdfs:comment	In general, a function approximation problem asks us to select a function among a well-defined class that closely matches ("approximates") a target function in a task-specific way. The need for function approximations arises in many branches of applied mathematics, and computer science in particular, such as predicting the growth of microbes in microbiology. Function approximations are used where theoretical models are unavailable or hard to compute. One can distinguish two major classes of function approximation problems: (en)
differentFrom	Function fitting
foaf:depiction
dct:subject	Regression analysis Statistical approximations
Wikipage page ID	336897 (xsd:integer)
Wikipage revision ID	1066689981 (xsd:integer)
Link from a Wikipage to another Wikipage	Regression analysis Applied mathematics Approximation theory Interpolation Radial basis function network Function (mathematics) Computer science Kriging Statistical approximations Domain of a function Curve fitting Numerical analysis Rational function Regression analysis Codomain Polynomial Special function Microbiology Real number Statistical classification Extrapolation Computational learning theory Fitness approximation Supervised learning Least squares (function approximation)
sameAs	Function approximation Function approximation Function approximation Function approximation Function approximation Function approximation Function approximation
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thumbnail	wiki-commons:Special:FilePath/Step_function_approximation.png?width=300
date	January 2022 (en)
reason	Find a source that actually explicitly makes this kind of definition; this one doesn't quite do so (en)
has abstract	In general, a function approximation problem asks us to select a function among a well-defined class that closely matches ("approximates") a target function in a task-specific way. The need for function approximations arises in many branches of applied mathematics, and computer science in particular, such as predicting the growth of microbes in microbiology. Function approximations are used where theoretical models are unavailable or hard to compute. One can distinguish two major classes of function approximation problems: First, for known target functions approximation theory is the branch of numerical analysis that investigates how certain known functions (for example, special functions) can be approximated by a specific class of functions (for example, polynomials or rational functions) that often have desirable properties (inexpensive computation, continuity, integral and limit values, etc.). Second, the target function, call it g, may be unknown; instead of an explicit formula, only a set of points of the form (x, g(x)) is provided. Depending on the structure of the domain and codomain of g, several techniques for approximating g may be applicable. For example, if g is an operation on the real numbers, techniques of interpolation, extrapolation, regression analysis, and curve fitting can be used. If the codomain (range or target set) of g is a finite set, one is dealing with a classification problem instead. To some extent, the different problems (regression, classification, fitness approximation) have received a unified treatment in statistical learning theory, where they are viewed as supervised learning problems. (en)
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is Link from a Wikipage to another Wikipage of	Q-learning Neural network Alfréd Haar Approximation theory Vadim G. Vizing Intelligent control Interpolation Sparse distributed memory Proto-value function Radial basis function network Glossary of artificial intelligence Adaptive quadrature Fuzzy control system Learning classifier system Least-squares function approximation Paraconsistent logic Curve fitting Caren Diefenderfer Diffuse element method Jorge Stolfi Regression analysis Technical analysis Artificial neural network Regularization by spectral filtering Artificial neuron

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