hypothesis.html

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<DD>Returns the label index the hypothesis predicts.
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<A NAME="getLabel()"><!-- --></A><H3>
getLabel</H3>
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public <A HREF="../../../../../../com/rapidminer/example/Attribute.html" title="interface in com.rapidminer.example">Attribute</A> <B>getLabel</B>()</PRE>
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<DD>Returns the label.
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<A NAME="reset()"><!-- --></A><H3>
reset</H3>
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public void <B>reset</B>()</PRE>
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<DD>Sets 'coveredWeight' and 'positiveWeight' back to 0.0d.
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<A NAME="getCoveredWeight()"><!-- --></A><H3>
getCoveredWeight</H3>
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public double <B>getCoveredWeight</B>()</PRE>
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<DD>Returns the covered weight of this hypothesis.
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<A NAME="setCoveredWeight(double)"><!-- --></A><H3>
setCoveredWeight</H3>
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public void <B>setCoveredWeight</B>(double&nbsp;value)</PRE>
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<DD>Sets the covered weight of this hypothesis.
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<A NAME="getPositiveWeight()"><!-- --></A><H3>
getPositiveWeight</H3>
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public double <B>getPositiveWeight</B>()</PRE>
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<DD>Returns the covered positive weight of this hypothesis.
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<A NAME="setPositiveWeight(double)"><!-- --></A><H3>
setPositiveWeight</H3>
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public void <B>setPositiveWeight</B>(double&nbsp;value)</PRE>
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<DD>Sets the covered positive weight of this hypothesis.
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<A NAME="apply(com.rapidminer.example.Example)"><!-- --></A><H3>
apply</H3>
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public abstract void <B>apply</B>(<A HREF="../../../../../../com/rapidminer/example/Example.html" title="class in com.rapidminer.example">Example</A>&nbsp;e)</PRE>
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<DD>Hypothesis is applied to the example and internal statistics of the hypothesis are updated.
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<A NAME="applicable(com.rapidminer.example.Example)"><!-- --></A><H3>
applicable</H3>
<PRE>
public abstract boolean <B>applicable</B>(<A HREF="../../../../../../com/rapidminer/example/Example.html" title="class in com.rapidminer.example">Example</A>&nbsp;e)</PRE>
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<DD>Tests if the hypothesis is applicable to the example without updating the internal statistics of the hypothesis.
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<A NAME="refine()"><!-- --></A><H3>
refine</H3>
<PRE>
public abstract java.util.LinkedList&lt;<A HREF="../../../../../../com/rapidminer/operator/learner/igss/hypothesis/Hypothesis.html" title="class in com.rapidminer.operator.learner.igss.hypothesis">Hypothesis</A>&gt; <B>refine</B>()</PRE>
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<DD>Generates new hypothesis by adding one degree of complexity and creating all rules that are possible now.
 Classes extending this abstract class define the way the hypothesis are generated by the IGSS alsgorithm by
 implementing the refine() method. Be sure to avoid the creation of duplicate hypothesis, for example
 by overwriting and using the equals method.
 For example refine could increase the allowed depth of a decision tree or the number of literals of a conjunctive rule.
 Must return null if the hypothesis cannot be refined any more.
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<A NAME="canBeRefined()"><!-- --></A><H3>
canBeRefined</H3>
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public abstract boolean <B>canBeRefined</B>()</PRE>
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<DD>Returns true only if this hypothesis can still be refined.
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<A NAME="init(int)"><!-- --></A><H3>
init</H3>
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public abstract java.util.LinkedList&lt;<A HREF="../../../../../../com/rapidminer/operator/learner/igss/hypothesis/Hypothesis.html" title="class in com.rapidminer.operator.learner.igss.hypothesis">Hypothesis</A>&gt; <B>init</B>(int&nbsp;minComplexity)</PRE>
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<DD>Used to generate the first hypothesis or the first group of hypothesis.
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<A NAME="getComplexity()"><!-- --></A><H3>
getComplexity</H3>
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public abstract int <B>getComplexity</B>()</PRE>
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<DD>Returns complexity of the hypothesis.
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