Assume that for each training data point xi, its output value yi is observed. However in...

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Assume that for each training data point xi, its output value yi is observed. However in some situations that we can not measure the exact value of yi. Instead we only have information about if yi is larger or less than some value zi. More specifically, the training data is given a triplet (xi, zi .bi), where xi is represented by a vector (xi) = (00(xi), .. oM−1(xi))T; • zi € R is a scalar, bi € (0, 1) is a binary variable indicating that if the true output yi is larger than zi (bi = 1) or not (bi = 0). 1 Develop a regression model for the ambiguous training data (xi, zi, bi), i = 1, ..., n. Assume that for each training data point xi, its output value yi is observed. However in some situations that we can not measure the exact value of yi. Instead we only have information about if yi is larger or less than some value zi. More specifically, the training data is given a triplet (xi, zi .bi), where xi is represented by a vector (xi) = (00(xi), .. oM−1(xi))T; • zi € R is a scalar, bi € (0, 1) is a binary variable indicating that if the true output yi is larger than zi (bi = 1) or not (bi = 0). 1 Develop a regression model for the ambiguous training data (xi, zi, bi), i = 1, ..., n.

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The problem described is a type of regression problem known as quantile regression In quantile regre... View the full answer