APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]


True


False


Either A or B


None of the above

Detailed explanation1: The predicted value of Y is called the predicted value of Y, and is denoted Y’. The difference between the observed Y and the predicted Y (YY’) is called a residual. The predicted Y part is the linear part. The residual is the error.
Detailed explanation2: In linear regression, a residual is the difference between the actual value and the value predicted by the model (yŷ) for any given point. A leastsquares regression model minimizes the sum of the squared residuals.
Detailed explanation3: The difference between the actual value of the dependent variable y (in the sample date) and the predicted value of the dependent variable ^y obtained from the linear regression equation is called the error or residual.