Multiple choice problem regarding linear regression model. Does anyone suggest a
ID: 3149692 • Letter: M
Question
Multiple choice problem regarding linear regression model. Does anyone suggest a solution on how to tackle this problem? Thanks a lot
1. This problem deals with linear regression. Consider the following data set, the input variable (first column) indicates the amount spent by an individual on internet service and the output variable (second column) indicates the degree of satisfaction with his her internet service. Time spent Satisfaction Degree 11 18 17 10 15 12 19 10 We are interested in choosing the best weight vector among four candidates. The fourth candidate (w) uses higher-order features 1.xx For all others we assume that first component of the weight vector corresponds to the bias intercept term. We assume that the variance for each y is same (0.01) for all choices of the weights. We assume a Gaussian prior on the weight vectors with 0 mean and a diagonal covariance matrix with 0.01 at every diagonal entry. The candidates are: • 1 = (030, 050) • W 2 = (5.75, 0.04) • w= (3.20, 0.20) • = (8.75, -0.50, 0.02) Given the following statements: 1. Among the first three weights, wh will be the best estimate in terms of likelihood of the given data. 2. Among the first three weights, w) will be the best estimate in terms of likelihood of the given data. 3. Among all four weights, w, will be the best estimate in terms of likelihood of the given data. 4. Among all four weights, w will be the best estimate in terms of likelihood of the given data. 5. w) has the highest posterior 6. W, has the highest posterior 7. Ridge regression will always choose a non-linear mapping on features over the raw linear featureExplanation / Answer
which are true?
statement 1 4 and 7 are ture
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