abstractutility.html

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<TD><CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html#getUpperBound(double, double, com.rapidminer.operator.learner.igss.hypothesis.Hypothesis, double)">getUpperBound</A>, <A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html#utility(double, double, com.rapidminer.operator.learner.igss.hypothesis.Hypothesis)">utility</A></CODE></TD>
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<A NAME="priors"><!-- --></A><H3>
priors</H3>
<PRE>
protected double[] <B>priors</B></PRE>
<DL>
<DD>The prior probability of the two classes of the label.
<P>
<DL>
</DL>
</DL>
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<A NAME="large"><!-- --></A><H3>
large</H3>
<PRE>
protected int <B>large</B></PRE>
<DL>
<DD>The number of covered examples before normal approximation is used.
<P>
<DL>
</DL>
</DL>

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<A NAME="AbstractUtility(double[], int)"><!-- --></A><H3>
AbstractUtility</H3>
<PRE>
public <B>AbstractUtility</B>(double[]&nbsp;priors,
                       int&nbsp;large)</PRE>
<DL>
<DD>Constructor for all utilities.
<P>
</DL>

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<A NAME="calculateM(double, double)"><!-- --></A><H3>
calculateM</H3>
<PRE>
public double <B>calculateM</B>(double&nbsp;delta,
                         double&nbsp;epsilon)</PRE>
<DL>
<DD>Calculates the M-value needed for the GSS algorithm.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html#calculateM(double, double)">calculateM</A></CODE> in interface <CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html" title="interface in com.rapidminer.operator.learner.igss.utility">Utility</A></CODE></DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="confidenceIntervall(double, double)"><!-- --></A><H3>
confidenceIntervall</H3>
<PRE>
public double <B>confidenceIntervall</B>(double&nbsp;totalWeight,
                                  double&nbsp;delta)</PRE>
<DL>
<DD>Calculates the the unspecific confidence intervall.
  Uses Chernoff bounds if the number of random experiments is too small and normal approximatione otherwise.
  Considers the number of examples as the number of random experiments. problematic for g*(p-p0)) hypothesis, 
  that only cover a small amount of examples. No normal approximation should be used in this case.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html#confidenceIntervall(double, double)">confidenceIntervall</A></CODE> in interface <CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html" title="interface in com.rapidminer.operator.learner.igss.utility">Utility</A></CODE></DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="confidenceIntervall(double, double, com.rapidminer.operator.learner.igss.hypothesis.Hypothesis, double)"><!-- --></A><H3>
confidenceIntervall</H3>
<PRE>
public double <B>confidenceIntervall</B>(double&nbsp;totalWeight,
                                  double&nbsp;totalPositiveWeight,
                                  <A HREF="../../../../../../com/rapidminer/operator/learner/igss/hypothesis/Hypothesis.html" title="class in com.rapidminer.operator.learner.igss.hypothesis">Hypothesis</A>&nbsp;hypo,
                                  double&nbsp;delta)</PRE>
<DL>
<DD>Calculates the the confidence intervall for a specific hypothesis. 
  Uses Chernoff bounds if the number of random experiments is too small and normal approximation otherwise.
  This method is adapted for g*(p-p0) utility types. Every example for that the rule is applicable is one random experiment. 
  Should be overwritten by subclasses if they make a different random experiment.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html#confidenceIntervall(double, double, com.rapidminer.operator.learner.igss.hypothesis.Hypothesis, double)">confidenceIntervall</A></CODE> in interface <CODE><A HREF="../../../../../../com/rapidminer/operator/learner/igss/utility/Utility.html" title="interface in com.rapidminer.operator.learner.igss.utility">Utility</A></CODE></DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="confSmallM(double, double)"><!-- --></A><H3>
confSmallM</H3>
<PRE>
public abstract double <B>confSmallM</B>(double&nbsp;totalWeight,
                                  double&nbsp;delta)</PRE>
<DL>
<DD>Calculates the confidence intervall for small numbers of examples.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="conf(double, double)"><!-- --></A><H3>
conf</H3>
<PRE>
public abstract double <B>conf</B>(double&nbsp;totalWeight,
                            double&nbsp;delta)</PRE>
<DL>
<DD>Calculates the normal approximation of the confidence intervall.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="conf(double, double, com.rapidminer.operator.learner.igss.hypothesis.Hypothesis, double)"><!-- --></A><H3>
conf</H3>
<PRE>
public abstract double <B>conf</B>(double&nbsp;totalWeight,
                            double&nbsp;totalPositiveWeight,
                            <A HREF="../../../../../../com/rapidminer/operator/learner/igss/hypothesis/Hypothesis.html" title="class in com.rapidminer.operator.learner.igss.hypothesis">Hypothesis</A>&nbsp;hypo,
                            double&nbsp;delta)</PRE>
<DL>
<DD>Calculates the normal approximation of the confidence intervall for a specific hypothesis.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="inverseNormal(double)"><!-- --></A><H3>
inverseNormal</H3>
<PRE>
public double <B>inverseNormal</B>(double&nbsp;p)</PRE>
<DL>
<DD>Calculates the inverse of the normal distribution, e.g.inverseNormal(0.95)==1.64.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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