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What is an advantage of using polynomial regression over linear regression.
Why is it possible to model non-linear functions with polynomial regression?
What are the shortcomings of using polynomial regression? Select all that apply.
For a multivariate linear regression problem with multivariate output , the loss function is minimised with respect to the weight matrix by setting the partial derivative . Which of the following terms is used to denote the partial derivative matrix, in such a scenario?
For a multivariate linear regression problem, the loss function is minimized with respect to the weight vector by setting the partial derivative . Which of the following correctly shows the expansion of the partial derivative, ?
In the closed form solution to multivariate linear regression, why do we use the pseudo-inverse of instead of the simple inverse?
An engineer has IID Gaussian observations where both and are unknown. The engineer makes the following argument:
"The standardised sample mean is standard normal. Therefore, I can replace the unknown by the sample standard deviation and obtain the exact confidence interval Afterall, since the chi-squared confidence interval for is exact for a Gaussian population, this substitution must also be exact."
Which assessment is correct?
The measurement errors from two sensing channels are modelled by the jointly Gaussian random vector
where the first argument of is the mean vector , and the second argument of is the covariance matrix . Using the formula for the joint Gaussian PDF from Slide 8 of this week's video, calculate the joint density at Give your answer as a decimal to at least three decimal places.