least squares

İngilizce - Türkçe

least squares teriminin İngilizce Türkçe sözlükte anlamı: (Bilgisayar) en küçük kareler
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

İngilizce - İngilizce

least squares teriminin İngilizce İngilizce sözlükte anlamı: (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
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