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State-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) <doi:10.1145/2576868>, with functions for prediction, model evaluation and inspection.

Mihaljevic Bojan

bnclassify

Learning Discrete Bayesian Network Classifiers from Data

Bielza Concha

Larranaga Pedro

Wickham Hadley

map function

<dl><dt>pred</dt>
<dd>A numeric matrix. Each row corresponds to class posterior 
probabilities for an instance.</dd></dl>

Arguments

Assigns instances to the most likely class. — map

<dl>

<dt>pred</dt>
<dd>A numeric matrix. Each row corresponds to class posterior 
probabilities for an instance.</dd>

</dl>

map: Assigns instances to the most likely class.

Description

Usage

Value

Arguments