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
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
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
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 square
Türkçe nasıl söylenir
list skwer
Telaffuz
/ˈlēst ˈskwer/ /ˈliːst ˈskwɛr/
Etimoloji
[ 'lEst ] (adjective, superlative of .) before 12th century. Middle English leest, from Old English l[AE]st, superlative of l[AE]ssa less.