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I need help in python without using sklearn, only using pandas, numpy and matplotlib You need to use 5-fold cross-validation to pick out the best

I need help in python without using sklearn, only using pandas, numpy and matplotlib

You need to use 5-fold cross-validation to pick out the best model for the prediction. You should present a chart of the error function J, similar to the one in the lecture (see below). You may need to use a package like "tabulate" to print out the table.

Ex.

image text in transcribed

You need to plot your training and testing J with respect to the polynomial degree, similar to the one in the lecture. ######################################################################

# TODO: 5-fold cross-validation #

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pass

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# END OF YOUR CODE #

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# TODO: Print out the table chart #

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pass ######################################################################

# END OF YOUR CODE #

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# TODO: Plot the J curve #

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pass

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# END OF YOUR CODE #

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\begin{tabular}{lrrrr} & Linear & Quadratic & Cubic & Fourth \\ \hline 1234 & 10.25 & 24.25 & 12.25 & 23.25 \\ 5 & 10.25 & 19.25 & 14.25 & 23.25 \\ 1235 & 10.25 & 15.25 & 19.25 & 23.25 \\ 4 & 10.25 & 10.25 & 20.25 & 23.25 \\ 1245 & 10.25 & 24.25 & 12.25 & 23.25 \\ 3 & 10.25 & 19.25 & 14.25 & 23.25 \\ 1345 & 10.25 & 24.25 & 12.25 & 23.25 \\ 2 & 10.25 & 19.25 & 14.25 & 23.25 \\ 2345 & 10.25 & 24.25 & 12.25 & 23.25 \\ 1 & 10.25 & 19.25 & 14.25 & 23.25 \\ Mean for Training & 0 & 0 & 0 & 0 \\ Mean for Testing & 0 & 0 & 0 & 0 \end{tabular}

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