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- Smoothing abstract "In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points (presumably because of noise) are reduced, and points that are lower than the adjacent points are increased leading to a smoother signal. Smoothing may be used in two important ways that can aid in data analysis (1) by being able to extract more information from the data as long as the assumption of smoothing is reasonable and (2) by being able to provide analyses that are both flexible and robust. Many different algorithms are used in smoothing. Data smoothing is typically done through the simplest of all density estimators, the histogram. Smoothing may be distinguished from the related and partially overlapping concept of curve fitting in the following ways: curve fitting often involves the use of an explicit function form for the result, whereas the immediate results from smoothing are the "smoothed" values with no later use made of a functional form if there is one; the aim of smoothing is to give a general idea of relatively slow changes of value with little attention paid to the close matching of data values, while curve fitting concentrates on achieving as close a match as possible. smoothing methods often have an associated tuning parameter which is used to control the extent of smoothing. Curve fitting will adjust any number of parameter of the function to obtain the 'best' fit.However, the terminology used across applications is mixed. For example, use of an interpolating spline fits a smooth curve exactly through the given data points and is sometimes called "smoothing".[citation needed]".
- Smoothing wikiPageExternalLink smoothing-filtering-and-prediction-estimating-the-past-present-and-future.
- Smoothing wikiPageID "4155662".
- Smoothing wikiPageRevisionID "596415449".
- Smoothing hasPhotoCollection Smoothing.
- Smoothing subject Category:Data_analysis.
- Smoothing subject Category:Image_processing.
- Smoothing subject Category:Signal_processing.
- Smoothing subject Category:Statistical_charts_and_diagrams.
- Smoothing subject Category:Time_series_analysis.
- Smoothing type Abstraction100002137.
- Smoothing type Chart106999802.
- Smoothing type Communication100033020.
- Smoothing type StatisticalChartsAndDiagrams.
- Smoothing type VisualCommunication106873252.
- Smoothing comment "In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. In smoothing, the data points of a signal are modified so individual points (presumably because of noise) are reduced, and points that are lower than the adjacent points are increased leading to a smoother signal.".
- Smoothing label "Alisado".
- Smoothing label "Glätten (Mathematik)".
- Smoothing label "Lissage (mathématiques)".
- Smoothing label "Smoothing".
- Smoothing label "Smoothing".
- Smoothing label "平滑".
- Smoothing sameAs Glätten_(Mathematik).
- Smoothing sameAs Alisado.
- Smoothing sameAs Lissage_(mathématiques).
- Smoothing sameAs Smoothing.
- Smoothing sameAs m.0bm3qk.
- Smoothing sameAs Q775963.
- Smoothing sameAs Q775963.
- Smoothing sameAs Smoothing.
- Smoothing wasDerivedFrom Smoothing?oldid=596415449.
- Smoothing isPrimaryTopicOf Smoothing.