Class Learner

  extended by
All Implemented Interfaces:
Direct Known Subclasses:
ParameterLearner, StructureLearner

public abstract class Learner
extends java.lang.Object
implements ModelComponent

This abstract class is the common ancestor for all specific model-learners. A learner's main purpose is to provide the method "learnModel" which takes a list of atom expressions (the data) and learns a knowledge base of the given type out of them. For each model type that provides at least one learning algorithm a specific learner has to be implemented.
The task of learning a knowledge base can be divided into structure learning and parameter learning. For both of these tasks abstract learners are available that can be employed for implementing a specific approach.

Matthias Thimm

Constructor Summary
Method Summary
 java.util.List<AtomExpression> incorporateClosedWorldAssumption(java.util.Collection<? extends AtomExpression> samples)
          This method incorporates a closed world assumption into the given set of samples.
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface
getDescription, getId, getSupportedKnowledgeBaseClass

Constructor Detail


public Learner()
Method Detail


public java.util.List<AtomExpression> incorporateClosedWorldAssumption(java.util.Collection<? extends AtomExpression> samples)
This method incorporates a closed world assumption into the given set of samples. This means, for every boolean predicate "p" of arity "n" appearing in "samples" and any n-vector "[c1,...,cn]" of constants appearing in "samples": if "p(c1,...,cn)=true" is not in "samples" then "p(c1,...,cn)=false" is added.

samples - a collection of atom expression.
a set of atom expressions that consists of all atom expressions in "samples" and every "p(c1,...,cn)=false" such that "p(c1,...,cn)=true" is not in "samples".