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Add line break to adhere to 80 character line limit
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source/classification2.Rmd

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@@ -1233,7 +1233,9 @@ validation accuracy estimate varies only by around `r round(3*sd(100*accuracies$
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each estimate having a standard error around `r round(mean(100*accuracies$std_err), 0)`%.
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Since the cross-validation accuracy estimates the test set accuracy,
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the fact that the test set accuracy also doesn't change much is expected.
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Also note that the $K =$ 3 model had a precision of `r round(100*cancer_prec_1$.estimate, 0)`% and recall of `r round(100*cancer_rec_1$.estimate, 0)`%,
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Also note that the $K =$ 3 model had
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a precision of `r round(100*cancer_prec_1$.estimate, 0)`% and
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recall of `r round(100*cancer_rec_1$.estimate, 0)`%,
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while the tuned model had
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a precision of `r round(100*cancer_prec_tuned, 0)`% and recall of `r round(100*cancer_rec_tuned, 0)`%.
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Given that the recall decreased—remember, in this application, recall

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