constructiveregression.html

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<B>Constructor Detail</B></FONT></TH>
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<A NAME="ConstructiveRegression(com.rapidminer.operator.learner.functions.kernel.rvm.RegressionProblem, com.rapidminer.operator.learner.functions.kernel.rvm.Parameter)"><!-- --></A><H3>
ConstructiveRegression</H3>
<PRE>
public <B>ConstructiveRegression</B>(<A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/rvm/RegressionProblem.html" title="class in com.rapidminer.operator.learner.functions.kernel.rvm">RegressionProblem</A>&nbsp;problem,
                              <A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/rvm/Parameter.html" title="class in com.rapidminer.operator.learner.functions.kernel.rvm">Parameter</A>&nbsp;parameter)</PRE>
<DL>
<DD>Constructor
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<A NAME="convertListToDoubleArray(java.util.List)"><!-- --></A><H3>
convertListToDoubleArray</H3>
<PRE>
protected double[] <B>convertListToDoubleArray</B>(java.util.List&nbsp;list)</PRE>
<DL>
<DD>Take a list holding "Double"-objects and return an "double[]"
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="innerProduct(double[], double[])"><!-- --></A><H3>
innerProduct</H3>
<PRE>
protected double <B>innerProduct</B>(double[]&nbsp;x,
                              double[]&nbsp;y)</PRE>
<DL>
<DD>Return the inner product of x and y (x.length == y.length assumed)
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="prune(java.util.LinkedList)"><!-- --></A><H3>
prune</H3>
<PRE>
protected void <B>prune</B>(java.util.LinkedList&lt;java.lang.Integer&gt;&nbsp;basisSet)</PRE>
<DL>
<DD>Create pruned versions of all important matrices / vectors so that 
  only rows / columns matching the indices in basisSet are kept.
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="updateSIGMA()"><!-- --></A><H3>
updateSIGMA</H3>
<PRE>
protected void <B>updateSIGMA</B>()</PRE>
<DL>
<DD>Update the covariance Matrix of the weight posterior distribution (SIGMA)
  along with its cholesky factor:
  
  SIGMA = (A + beta * PHI^t * PHI)^{-1}
  
  SIGMA_chol with SIGMA_chol * SIGMA_chol^t = SIGMA
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="updateMu()"><!-- --></A><H3>
updateMu</H3>
<PRE>
protected void <B>updateMu</B>()</PRE>
<DL>
<DD>Update the mean of the weight posterior distribution (mu):
  
  mu = beta * SIGMA * PHI^t * t
<P>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="updateCriteriumScalars(int)"><!-- --></A><H3>
updateCriteriumScalars</H3>
<PRE>
protected void <B>updateCriteriumScalars</B>(int&nbsp;selectedBasis)</PRE>
<DL>
<DD>Compute the scalars s_m, q_m which are part of the criterium for 
  inclusion / deletion of the given basis m:
 
  S_m = beta * phi^t_m * phi_m  - beta^2 * phi^t_m * PHI * SIGMA * PHI^t * phi_m
  Q_m = beta * phi^t_m * t              - beta^2 * phi^t_m * PHI * SIGMA * PHI^t * t
  
  s_m = alpha_m * S_m / (alpha_m - S_m)
  q_m = alpha_m * Q_m / (alpha_m - S_m)
<P>
<DD><DL>
</DL>
</DD>
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<A NAME="reestimateAlpha(int)"><!-- --></A><H3>
reestimateAlpha</H3>
<PRE>
protected void <B>reestimateAlpha</B>(int&nbsp;selectedBasis)</PRE>
<DL>
<DD>Reestimate alpha by setting it to the value which maximizes the
  marginal likelihood:
  
  alpha_i = s^2_i / (q^2_i - s_i)
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="includeBasis(int)"><!-- --></A><H3>
includeBasis</H3>
<PRE>
protected void <B>includeBasis</B>(int&nbsp;selectedBasis)</PRE>
<DL>
<DD>Include a basis function into the model.
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="deleteBasis(int)"><!-- --></A><H3>
deleteBasis</H3>
<PRE>
protected void <B>deleteBasis</B>(int&nbsp;selectedBasis)</PRE>
<DL>
<DD>Delete a basis function from the model.
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="updateBeta()"><!-- --></A><H3>
updateBeta</H3>
<PRE>
protected void <B>updateBeta</B>()</PRE>
<DL>
<DD>Update beta (same as for the "normal" regression rvm)
<P>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="learn()"><!-- --></A><H3>
learn</H3>
<PRE>
public <A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/rvm/Model.html" title="class in com.rapidminer.operator.learner.functions.kernel.rvm">Model</A> <B>learn</B>()</PRE>
<DL>
<DD>The hard work is done here
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/rvm/RVMBase.html#learn()">learn</A></CODE> in class <CODE><A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/rvm/RVMBase.html" title="class in com.rapidminer.operator.learner.functions.kernel.rvm">RVMBase</A></CODE></DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Identify the RVM
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE>toString</CODE> in class <CODE>java.lang.Object</CODE></DL>
</DD>
<DD><DL>
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