Least Squares
Least Squares is a statistical method used to find the line of best fit for a set of data points. It is commonly used in regression analysis to determine the relationship between two variables. The method works by minimizing the sum of the squares of the differences between the observed values and the predicted values. This is done by finding the values of the coefficients that make the sum of the squares of the residuals as small as possible. The method can be used for both linear and nonlinear regression analysis. Least Squares is widely used in machine learning algorithms, such as linear regression, logistic regression, and support vector machines.
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