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AIMA-Java Core Algorithms from the book Artificial Intelligence a Modern Approach 3rd Ed.

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package aima.core.probability.bayes;

import aima.core.probability.CategoricalDistribution;
import aima.core.probability.Factor;
import aima.core.probability.proposition.AssignmentProposition;

/**
 * Artificial Intelligence A Modern Approach (3rd Edition): page 512.
*
* A Conditional Probability Table, or CPT, can be used for representing * conditional probabilities for discrete (finite) random variables. Each row in * a CPT contains the conditional probability of each node value for a * conditioning case. * * @author Ciaran O'Reilly */ public interface ConditionalProbabilityTable extends ConditionalProbabilityDistribution { @Override CategoricalDistribution getConditioningCase(Object... parentValues); @Override CategoricalDistribution getConditioningCase( AssignmentProposition... parentValues); /** * Construct a Factor consisting of the Random Variables from the * Conditional Probability Table that are not part of the evidence (see * AIMA3e pg. 524). * * @param evidence * @return a Factor for the Random Variables from the Conditional * Probability Table that are not part of the evidence. */ Factor getFactorFor(AssignmentProposition... evidence); }




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