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remove extra stuff about confusion matrix (we now have a better intro to that earlier in the chapter)
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source/classification2.Rmd

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@@ -514,10 +514,8 @@ In the metrics data frame, we filtered the `.metric` column since we are
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interested in the `accuracy` row. Other entries involve other metrics that
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are beyond the scope of this book. Looking at the value of the `.estimate` variable
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shows that the estimated accuracy of the classifier on the test data
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was `r round(100*cancer_acc_1$.estimate, 0)`%.
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We can also look at the *confusion matrix* for the classifier, which shows
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the table of predicted labels and correct labels, using the `conf_mat` function:
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was `r round(100*cancer_acc_1$.estimate, 0)`%. We can also look at the *confusion matrix* for
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the classifier using the `conf_mat` function.
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```{r 06-confusionmat}
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confusion <- cancer_test_predictions |>

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