least squares

listen to the pronunciation of least squares
English - Turkish
(Bilgisayar) en küçük kareler

Related Terms

least squares method
(Ticaret) en küçük kareler metodu
least squares curve
en küçük kareler eğrisi
least squares estimation
en küçük kareler kestirimi
least squares estimator
en kucuk kareler kestiricisi
least mean squares
(Bilgisayar) en küçük ortalama kareler
ordinary least squares
(Ticaret) en küçük kareler yöntemi
least square
en küçük kare
least mean squares
en kucuk ortalama kareler
method of least squares
en-küçük kareler yöntemi
English - English
(İstatistik) A method of determining the curve that best describes the relationship between expected and observed sets of data by minimizing the sums of the squares of deviation between observed and expected values
A criterion used to find the line of best fit, namely that the sum of the squares of the differences between "predicted values" and actual values should be as small as possible
An estimating model that determines parameter weights based on the set that minimizes the sum of the squared deviation of predicted values from a line or set of observed values
A forecasting method like regression analysis that selects a line of best fit through a scattering of data to minimize the sum of squares of the deviations of the given points from the forecast
a method of fitting a curve to data points so as to minimize the sum of the squares of the distances of the points from the curve
The most common method of training (estimating) the weights (parameters) of a model by choosing the weights that minimize the sum of the squared deviation of the predicted values of the model from the observed values of the data

Related Terms

least squares method
Statistical method for finding a line or curve the line of best fit that best represents a correspondence between two measured quantities (e.g., height and weight of a group of college students). When the measurements are plotted as points on a graph and seem to fall near the same line, the least squares method may be used to determine the best-fitting line. The method uses calculus techniques to find the minimum of the sum of the squares of the vertical distances of each data point from the proposed line. More generally, the process is called regression or, when the fitted curve is a line, linear regression
least squares
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