Homework 2: Read the posted handouts and solve the following problems. Problem 1: Want to predict house price based on some information about the house (location, number of rooms, etc.) Assume that you have a data for n houses. – x is a d dimensional vector of observations for house i Xi = (x, , Xi, , x,d): X is a d × n matrix of all houses. y is a vector of the price of each house y = (y1,y2, yn) y = WX, W is a 1 × d dimensional matrix – W that would result in a lowest error, i.e. smallest difference between predicted price and real price. Find the matrix W that provides the lowest error in the least-squares (LS) sense. Problem 2:

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