1. Load the cpus dataset from the MASS package. Use syct, mmin , mmax , cach...

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1. Load the cpus dataset from the MASS package.
Use syct, mmin , mmax , cach , chmin, chmax as the predictors(independent variables) to predict performance (perf)
Perform the best subset selection in order to choose the bestpredictors from the above predictors.
What is the best model obtained according to Cp, BIC, and adjustedR2?
Show some plots to provide evidence for your answer, and report thecoefficients of the best model obtained for each criterion.
Repeat using forward stepwise selection and also using backwardstepwise selection. How does your answer compare to the best subsetresults?

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CONSIDERING THE GIVEN PARAMETERS WE SHOW THE FOLL1 The library function loads a package into your workspacesuch aslibrary MASSIts going to be a MASS package The Boston data frame that canbe accessed immediately is already included in this package2 Predictive models are extremely helpful in R programming forpredicting future performance and estimating parameters that areimpractical to calculate For example predictive models may beused by data scientists to forecast crop yields based onprecipitation and temperature or to assess if patients withcertain See Answer

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