new_ml_model_naive_bayes <- function(pipeline_model, formula, dataset, label_col,
features_col, predicted_label_col) {
m <- new_ml_model_classification(
pipeline_model, formula,
dataset = dataset,
label_col = label_col, features_col = features_col,
predicted_label_col = predicted_label_col,
class = "ml_model_naive_bayes"
)
model <- m$model
pi <- model$pi
names(pi) <- m$index_labels
m$pi <- pi
theta <- model$theta
rownames(theta) <- m$index_labels
colnames(theta) <- m$feature_names
m$theta <- theta
m
}
# Generic implementations
#' @export
print.ml_model_naive_bayes <- function(x, ...) {
printf("A-priori probabilities:\n")
print(exp(sort_named_list(x$pi)))
print_newline()
printf("Conditional probabilities:\n")
print(exp(x$theta[order(row.names(x$theta)), ]))
print_newline()
x
}
#' @export
summary.ml_model_naive_bayes <- function(object, ...) {
print(object, ...)
}
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