APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -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 (Y-Y’) is called a residual. The predicted Y part is the linear part. The residual is the error.
Detailed explanation-2: -In linear regression, a residual is the difference between the actual value and the value predicted by the model (y-ŷ) for any given point. A least-squares regression model minimizes the sum of the squared residuals.
Detailed explanation-3: -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.