COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Detailed explanation-1: -How many coefficients do you need to estimate in a simple linear regression model (One independent variable)? In simple linear regression, there is one independent variable so 2 coefficients (Y=a+bx).
Detailed explanation-2: -With simple linear regression, there are only two regression coefficients-b0 and b1. There are only two normal equations.
Detailed explanation-3: -Simple linear regression formula y is the predicted value of the dependent variable (y) for any given value of the independent variable (x). B0 is the intercept, the predicted value of y when the x is 0. B1 is the regression coefficient – how much we expect y to change as x increases.
Detailed explanation-4: -They are classified into three. They are simple partial and multiple, positive and negative, and linear and non-linear. In the linear regression line, the equation is given by Y = b0 + b1X. Here b0 is a constant and b1 is the regression coefficient.
Detailed explanation-5: -Concept: The product of regression coefficient of y on x and regression coefficient of x on y is always less than or equal to 1. So b x y × b y x ≤ 1 where bxy and byx are coefficient of regression.