predict.bnc_fit: Predicts class labels or class posterior probability...

In bnclassify: Learning Discrete Bayesian Network Classifiers from Data

Predicts class labels or class posterior probability distributions.

Description

Predicts class labels or class posterior probability distributions.

Usage

## S3 method for class 'bnc_fit'
predict(object, newdata, prob = FALSE, ...)

Arguments

object	A bnc_bn object.
newdata	A data frame containing observations whose class has to be predicted.
prob	A logical. Whether class posterior probability should be returned.
...	Ignored.

Details

Ties are resolved randomly. Inference is much slower if newdata contains NAs.

Value

If prob=FALSE, then returns a length-N factor with the same levels as the class variable in x, where N is the number of rows in newdata. Each element is the most likely class for the corresponding row in newdata. If prob=TRUE, returns a N by C numeric matrix, where C is the number of classes; each row corresponds to the class posterior of the instance.

Examples

data(car)
nb <- bnc('nb', 'class', car, smooth = 1)
p <- predict(nb, car)
head(p)
p <- predict(nb, car, prob = TRUE)
head(p)

bnclassify documentation built on June 22, 2024, 11:08 a.m.