The creation of a curved line, often based on a nonlinear regression model, that best represents a set of data points.
The attempt to find a pattern in data by drawing a line through a set of points so that it goes as close as possible to all of them. This could be a straight line but is more generally a curved one, ideally with an underlying equation which would help to analyse the data.
An automated mapping function that converts a series of short connected straight lines into smooth curves to represented entities that do not have precise mathematical definitions (such as rivers, shorelines, and contour lines).
Curve fitting is the process of computing the coefficients of a function to approximate the values of a given data set within that function. The approximation is called a "fit". A mathematical function, such as a least squares regression, is used to judge the accuracy of the fit.
Generation of a fitted curve which passes through or nearby all given points. Spline curve or B Spline curve is a popular curve fitting.
The derivation of an analytic function () with its graph = () passing through or approximately through a finite set of data points (, ), . Curve-fitting procedures include interpolation, in which case () = for each data point, and the least squares method, in which case the derived function minimizes the sum of the squares of the differences between () and over all the data points. The functions used in curve fitting are usually polynomials. In least squares methods, a single polynomial of low degree typically is used over the entire range of spanned by the data; in interpolation procedures, a separate polynomial typically is defined over each subinterval and the polynomial pieces connected through imposition of certain continuity conditions. See spline function.
Curve fitting is finding a curve which matches a series of data points and possibly other constraints. This section is an introduction to both interpolation (where an exact fit to constraints is expected) and curve fitting/regression analysis (where an approximate fit is permitted).