Tidy a(n) confusionMatrix object
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'confusionMatrix' tidy(x, by_class = TRUE, ...)
x |
An object of class |
by_class |
Logical indicating whether or not to show performance
measures broken down by class. Defaults to |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
A tibble::tibble()
with columns:
class |
The class under consideration. |
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
estimate |
The estimated value of the regression term. |
term |
The name of the regression term. |
p.value |
P-value for accuracy and kappa statistics. |
if (requireNamespace("caret", quietly = TRUE)) { library(caret) set.seed(27) two_class_sample1 <- as.factor(sample(letters[1:2], 100, TRUE)) two_class_sample2 <- as.factor(sample(letters[1:2], 100, TRUE)) two_class_cm <- caret::confusionMatrix( two_class_sample1, two_class_sample2 ) tidy(two_class_cm) tidy(two_class_cm, by_class = FALSE) # multiclass example six_class_sample1 <- as.factor(sample(letters[1:6], 100, TRUE)) six_class_sample2 <- as.factor(sample(letters[1:6], 100, TRUE)) six_class_cm <- caret::confusionMatrix( six_class_sample1, six_class_sample2 ) tidy(six_class_cm) tidy(six_class_cm, by_class = FALSE) }
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