Consider a single-input single-output data set of the form ((xp, yp), p = 1, 2, ...,...

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Consider a single-input single-output data set of the form ((xp, yp), p = 1, 2, ..., 16): X=[xx [y y x=-2.12-1.1 -1 -0.9 -0.2 -0.1 0 0.1 0.9 1 1.1 1.9 2 2.1 3] 31][12 1 2 3 1 2 3 4 2 3 4 3455] (a) Apply least-squares linear regression to the data to generate a prediction model y=wx+b*. (b) In a single figure, plot the sixteen data samples and the optimized model y=wx+b' as a straight line in the x-y space. (c) Use the model obtain to predict the output for input x = 1.5. Consider a single-input single-output data set of the form ((xp, yp), p = 1, 2, ..., 16): X=[xx [y y x=-2.12-1.1 -1 -0.9 -0.2 -0.1 0 0.1 0.9 1 1.1 1.9 2 2.1 3] 31][12 1 2 3 1 2 3 4 2 3 4 3455] (a) Apply least-squares linear regression to the data to generate a prediction model y=wx+b*. (b) In a single figure, plot the sixteen data samples and the optimized model y=wx+b' as a straight line in the x-y space. (c) Use the model obtain to predict the output for input x = 1.5.

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The slope m and intercept b of a straight line determined through the leastsquares linear regression ... View the full answer