Posterior Classification Summaries for a Naive Bayes model

Given a set of observed data including a categorical response variable y and a naiveBayes model of y, this function returns summaries of the model's posterior classification quality. These summaries include a confusion matrix as well as an estimate of the model's overall accuracy.

naive_classification_summary(model, data, y)

Arguments

model

a naiveBayes model object with categorical y

data

data frame including the variables in the model

y

a character string indicating the y variable in data

Value

a list

Examples

data(penguins_bayes, package = "bayesrules")
example_model <- e1071::naiveBayes(species ~ bill_length_mm, data = penguins_bayes)
naive_classification_summary(model = example_model, data = penguins_bayes, y = "species")
#> $confusion_matrix
#>    species       Adelie Chinstrap       Gentoo
#>     Adelie 95.39% (145) 0.00% (0)  4.61%   (7)
#>  Chinstrap  5.88%   (4) 8.82% (6) 85.29%  (58)
#>     Gentoo  6.45%   (8) 4.84% (6) 88.71% (110)
#> 
#> $overall_accuracy
#> [1] 0.7587209
#>