Copy of Assignment 3.txt - display the dataset check the...

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### display the dataset, check the dimension of the dataset train test fix(train) fix(test) ### you can use "lm" function to model the data (x,y) using polynomials ### remember to specify your model using poly(x,d)where d is the highest degree of your desired degree of your polynomial model ### for example, poly(x, 2) will fit a model with quadratic coefficients ## poly(x, 1) shown below will fit a model with simple linear coefficients model <- lm(y ~ poly(x,1),data=train) ### you can look up for details of the model summary(model) model2 <- lm(y ~ poly(x,2),data=train) model3 <- lm(y ~ poly(x,3),data=train) model4 <- lm(y ~ poly(x,4),data=train) model5 <- lm(y ~ poly(x,5),data=train) summary(model2) summary(model3) summary(model4) summary(model5) ### compute the training error msetrain=mean((train$y-fitted(model))^2) msetrain2=mean((train$y-fitted(model2))^2) msetrain3=mean((train$y-fitted(model3))^2) msetrain4=mean((train$y-fitted(model4))^2) msetrain5=mean((train$y-fitted(model5))^2) ### use this model to fit data in test set
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