interpreting visual dis

George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2; When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten-fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset

30 points Save Answer interpreting visual dis George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2: When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten- fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). B I U Paragraph Arial 14px TX Q > TT 19 + E 0.) 30 points Save Answer interpreting visual dis George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2: When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten- fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). B I U Paragraph Arial 14px TX Q > TT 19 + E 0.)

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interpreting visual dis

George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2; When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten-fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset

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30 points Save Answer interpreting visual dis George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2: When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten- fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). B I U Paragraph Arial 14px TX Q > TT 19 + E 0.) 30 points Save Answer interpreting visual dis George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training error is 224.2: When George attempts cubic regression MSE for his training error is 67.5. On the other hand his ten- fold crossvalidation error for cubic regression is 323.6 and his cross validation error for linear regression is 293.3; What explains these results; which is the best model to use for this dataset For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). B I U Paragraph Arial 14px TX Q > TT 19 + E 0.)

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interpreting visual dis George has a dataset of eight data points with a single predictor variable. When he attempts linear regression MSE for his training

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