inspect_bnc_bn: Inspect a Bayesian network classifier (with structure and...

In bnclassify: Learning Discrete Bayesian Network Classifiers from Data

Inspect a Bayesian network classifier (with structure and parameters).

Description

Functions for inspecting a bnc_bn object. In addition, you can query this object with the functions documented in inspect_bnc_dag.

Usage

nparams(x)

manb_arc_posterior(x)

awnb_weights(x)

params(x)

values(x)

classes(x)

Arguments

x	The bnc_bn object. The Bayesian network classifier.

Functions

• nparams(): Returns the number of free parameters in the model.

• manb_arc_posterior(): Returns the posterior of each arc from the class according to the MANB method.

• awnb_weights(): Returns the AWNB feature weights.

• params(): Returns the list of CPTs, in the same order as vars.

• values(): Returns the possible values of each variable, in the same order as vars.

• classes(): Returns the possible values of the class variable.

Examples

 
data(car)
nb <- bnc('nb', 'class', car, smooth = 1)
nparams(nb)
nb <- bnc('nb', 'class', car, smooth = 1, manb_prior = 0.5)
manb_arc_posterior(nb)
nb <- bnc('nb', 'class', car, smooth = 1, awnb_bootstrap = 0.5)
awnb_weights(nb)

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