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<A NAME="KERNEL_DOT"><!-- --></A><H3>KERNEL_DOT</H3><PRE>public static final int <B>KERNEL_DOT</B></PRE><DL><DD>Indicates a linear kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_DOT">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_RADIAL"><!-- --></A><H3>KERNEL_RADIAL</H3><PRE>public static final int <B>KERNEL_RADIAL</B></PRE><DL><DD>Indicates a rbf kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_RADIAL">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_POLYNOMIAL"><!-- --></A><H3>KERNEL_POLYNOMIAL</H3><PRE>public static final int <B>KERNEL_POLYNOMIAL</B></PRE><DL><DD>Indicates a polynomial kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_POLYNOMIAL">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_SIGMOID"><!-- --></A><H3>KERNEL_SIGMOID</H3><PRE>public static final int <B>KERNEL_SIGMOID</B></PRE><DL><DD>Indicates a sigmoid kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_SIGMOID">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_ANOVA"><!-- --></A><H3>KERNEL_ANOVA</H3><PRE>public static final int <B>KERNEL_ANOVA</B></PRE><DL><DD>Indicates an anova kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_ANOVA">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_EPANECHNIKOV"><!-- --></A><H3>KERNEL_EPANECHNIKOV</H3><PRE>public static final int <B>KERNEL_EPANECHNIKOV</B></PRE><DL><DD>Indicates a Epanechnikov kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_EPANECHNIKOV">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_GAUSSIAN_COMBINATION"><!-- --></A><H3>KERNEL_GAUSSIAN_COMBINATION</H3><PRE>public static final int <B>KERNEL_GAUSSIAN_COMBINATION</B></PRE><DL><DD>Indicates a Gaussian combination kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_GAUSSIAN_COMBINATION">Constant Field Values</A></DL></DL><HR><A NAME="KERNEL_MULTIQUADRIC"><!-- --></A><H3>KERNEL_MULTIQUADRIC</H3><PRE>public static final int <B>KERNEL_MULTIQUADRIC</B></PRE><DL><DD>Indicates a multiquadric kernel.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../../../../constant-values.html#com.rapidminer.operator.learner.functions.kernel.functions.Kernel.KERNEL_MULTIQUADRIC">Constant Field Values</A></DL></DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="Kernel()"><!-- --></A><H3>Kernel</H3><PRE>public <B>Kernel</B>()</PRE><DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Method Detail</B></FONT></TH></TR></TABLE><A NAME="getType()"><!-- --></A><H3>getType</H3><PRE>public abstract int <B>getType</B>()</PRE><DL><DD>Must return one out of KERNEL_DOT, KERNEL_RADIAL, KERNEL_POLYNOMIAL, KERNEL_SIGMOID, KERNEL_ANOVA, KERNEL_EPANECHNIKOV, KERNEL_GAUSSIAN_COMBINATION, or KERNEL_MULTIQUADRIC.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="calculateDistance(double[], double[])"><!-- --></A><H3>calculateDistance</H3><PRE>public abstract double <B>calculateDistance</B>(double[] x1, double[] x2)</PRE><DL><DD>Subclasses must implement this method.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="init(com.rapidminer.example.ExampleSet)"><!-- --></A><H3>init</H3><PRE>public void <B>init</B>(<A HREF="../../../../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A> exampleSet)</PRE><DL><DD>Calculates all distances and store them in a matrix to speed up optimization.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="getDistance(int, int)"><!-- --></A><H3>getDistance</H3><PRE>public double <B>getDistance</B>(int x1, int x2)</PRE><DL><DD>Returns the distance between the examples with the given indices.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="getAttributeValues(int)"><!-- --></A><H3>getAttributeValues</H3><PRE>public double[] <B>getAttributeValues</B>(int i)</PRE><DL><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="innerProduct(double[], double[])"><!-- --></A><H3>innerProduct</H3><PRE>public double <B>innerProduct</B>(double[] x1, double[] x2)</PRE><DL><DD>Calculates the inner product of the given vectors.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="norm2(double[], double[])"><!-- --></A><H3>norm2</H3><PRE>public double <B>norm2</B>(double[] x1, double[] x2)</PRE><DL><DD>Calculates the L2-norm, i.e. ||x-y||^2.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="getSum(java.util.Collection, double[])"><!-- --></A><H3>getSum</H3><PRE>public double <B>getSum</B>(java.util.Collection supportVectors, double[] currentX)</PRE><DL><DD>Calculates w*x from the given support vectors using this kernel function.<P><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="createKernel(int)"><!-- --></A><H3>createKernel</H3><PRE>public static <A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/functions/Kernel.html" title="class in com.rapidminer.operator.learner.functions.kernel.functions">Kernel</A> <B>createKernel</B>(int kernelType)</PRE><DL><DD><DL></DL></DD><DD><DL></DL></DD></DL><HR><A NAME="createKernel(int, com.rapidminer.operator.Operator)"><!-- --></A><H3>createKernel</H3><PRE>public static <A HREF="../../../../../../../com/rapidminer/operator/learner/functions/kernel/functions/Kernel.html" title="class in com.rapidminer.operator.learner.functions.kernel.functions">Kernel</A> <B>createKernel</B>(int kernelType, <A HREF="../../../../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A> operator) throws <A HREF="../../../../../../../com/rapidminer/parameter/UndefinedParameterError.html" title="class in com.rapidminer.parameter">UndefinedParameterError</A></PRE><DL><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE><A HREF="../../../../../../../com/rapidminer/parameter/UndefinedParameterError.html" title="class in com.rapidminer.parameter">UndefinedParameterError</A></CODE></DL></DD></DL><!-- ========= END OF CLASS DATA ========= --><HR><!-- ======= START OF BOTTOM NAVBAR ====== --><A NAME="navbar_bottom"><!-- --></A><A HREF="#skip-navbar_bottom" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_bottom_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY=""> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../../../../../overview-summary.html"><FONT CLASS="NavBarFont1"><B>Overview</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-summary.html"><FONT 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