inspect_bnc_dag: Inspect a Bayesian network classifier structure.

In bnclassify: Learning Discrete Bayesian Network Classifiers from Data

Inspect a Bayesian network classifier structure.

Description

Functions for inspecting a bnc_dag object.

Usage

class_var(x)

features(x)

vars(x)

families(x)

modelstring(x)

feature_families(x)

narcs(x)

is_semi_naive(x)

is_anb(x)

is_nb(x)

is_ode(x)

Arguments

x	The bnc_dag object. The Bayesian network classifier structure.

Functions

• class_var: Returns the class variable.

• features: Returns the features.

• vars: Returns all variables (i.e., features + class).

• families: Returns the family of each variable.

• modelstring: Returns the model string of the network in bnlearn format (adding a space in between two families).

• feature_families: Returns the family of each feature.

• narcs: Returns the number of arcs.

• is_semi_naive: Returns TRUE if x is a semi-naive Bayes.

• is_anb: Returns TRUE if x is an augmented naive Bayes.

• is_nb: Returns TRUE if x is a naive Bayes.

• is_ode: Returns TRUE if x is a one-dependence estimator.

Examples

data(car)
nb <- bnc('nb', 'class', car, smooth = 1)
narcs(nb)
is_ode(nb)

bnclassify documentation built on Nov. 16, 2022, 5:08 p.m.