The best fit line method for data in Linear Regression?(1 Point)Least Square ErrorMaximum LikelihoodLogarithmic LossBoth A and B
Question
The best fit line method for data in Linear Regression?(1 Point)Least Square ErrorMaximum LikelihoodLogarithmic LossBoth A and B
Solution
The best fit line method for data in Linear Regression is the Least Square Error. This method minimizes the sum of the squares of the residuals (the differences between the observed and predicted values). It is the most common method used in Linear Regression. Maximum Likelihood is another method used to estimate the parameters of a statistical model. However, in the context of Linear Regression, the Least Square Error is the most commonly used. Therefore, the answer is "Both A and B".
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