cla_nb: Naive Bayes Classifier

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Naive Bayes Classifier

Description

Naive Bayes classification using e1071::naiveBayes.

Usage

cla_nb(attribute, slevels)

Arguments

attribute	attribute target to model building.
slevels	possible values for the target classification.

Details

Assumes conditional independence of features given the class label, enabling fast probabilistic classification.

Value

returns a classification object.

References

Mitchell, T. (1997). Machine Learning. McGraw‑Hill. (Naive Bayes)

Examples

data(iris)
slevels <- levels(iris$Species)
model <- cla_nb("Species", slevels)

# preparing dataset for random sampling
sr <- sample_random()
sr <- train_test(sr, iris)
train <- sr$train
test <- sr$test

model <- fit(model, train)

prediction <- predict(model, test)
predictand <- adjust_class_label(test[,"Species"])
test_eval <- evaluate(model, predictand, prediction)
test_eval$metrics

daltoolbox documentation built on Nov. 5, 2025, 7:09 p.m.