Faculty of Computers and InformationFaculty of Computers and Information(Computer Exercise)Department of Computer SciencePattern RecognitionA First Simulation Example on Designing and Assessing a Regression Func-tion•Generate one small (10 observations) training dataset from binormal distribution (representing a response and a pre-dictor) with mean vector (0,0)′, unit variance, andρ= 0.8.•Fit the data to a linear model, calculate the apparent MSE given by1NRSS.•Plot the linear model, the data, and the best regression function (which is the conditional expectation of a bivariatenormal) on the same graph.•Generate a large data set (1000 observations to represent the population) from the same distribution and calculate thetrue error rate (the MSE or the risk) of your model on this data set; we denote this byerrtr. This is the performanceconditional on the training set above. Obtain the performance of best regression function as well; denote it byerr∗.
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