bayesrules (version 0.0.2)

naive_classification_summary_cv: Cross-Validated Posterior Classification Summaries for a Naive Bayes model

Description

Given a set of observed data including a categorical response variable y and a naiveBayes model of y, this function returns a cross validated confusion matrix by which to assess the model's posterior classification quality.

Usage

naive_classification_summary_cv(model, data, y, k = 10)

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

k

the number of folds to use for cross validation

Value

a list

Examples

# NOT RUN {
data(penguins_bayes, package = "bayesrules")
example_model <- e1071::naiveBayes(species ~ bill_length_mm, data = penguins_bayes)
naive_classification_summary_cv(model = example_model, data = penguins_bayes, y = "species", k = 2)
# }