svm.xml

SVM的一个源程序

<?xml version="1.0"?>
<doc>
    <assembly>
        <name>SVM</name>
    </assembly>
    <members>
        <member name="T:SVM.RangeTransform">
            <summary>
            Class which encapsulates a range transformation.
            </summary>
        </member>
        <member name="T:SVM.IRangeTransform">
            <summary>
            Interface implemented by range transforms.
            </summary>
        </member>
        <member name="M:SVM.IRangeTransform.Transform(System.Double,System.Int32)">
            <summary>
            Transform the input value using the transform stored for the provided index.
            </summary>
            <param name="input">Input value</param>
            <param name="index">Index of the transform to use</param>
            <returns>The transformed value</returns>
        </member>
        <member name="M:SVM.IRangeTransform.Transform(SVM.Node[])">
            <summary>
            Transforms the input array.
            </summary>
            <param name="input">The array to transform</param>
            <returns>The transformed array</returns>
        </member>
        <member name="M:SVM.RangeTransform.#ctor(System.Double[],System.Double[],System.Double,System.Double)">
            <summary>
            Constructor.
            </summary>
            <param name="minValues">The minimum values in each dimension.</param>
            <param name="maxValues">The maximum values in each dimension.</param>
            <param name="lowerBound">The desired lower bound for all dimensions.</param>
            <param name="upperBound">The desired upper bound for all dimensions.</param>
        </member>
        <member name="M:SVM.RangeTransform.Transform(SVM.Node[])">
            <summary>
            Transforms the input array based upon the values provided.
            </summary>
            <param name="input">The input array</param>
            <returns>A scaled array</returns>
        </member>
        <member name="M:SVM.RangeTransform.Transform(System.Double,System.Int32)">
            <summary>
            Transforms this an input value using the scaling transform for the provided dimension.
            </summary>
            <param name="input">The input value to transform</param>
            <param name="index">The dimension whose scaling transform should be used</param>
            <returns>The scaled value</returns>
        </member>
        <member name="M:SVM.RangeTransform.Write(System.IO.Stream,SVM.RangeTransform)">
            <summary>
            Writes this Range transform to a stream.
            </summary>
            <param name="stream">The stream to write to</param>
            <param name="r">The range to write</param>
        </member>
        <member name="M:SVM.RangeTransform.Write(System.String,SVM.RangeTransform)">
            <summary>
            Writes this Range transform to a file.    This will overwrite any previous data in the file.
            </summary>
            <param name="outputFile">The file to write to</param>
            <param name="r">The Range to write</param>
        </member>
        <member name="M:SVM.RangeTransform.Read(System.String)">
            <summary>
            Reads a Range transform from a file.
            </summary>
            <param name="inputFile">The file to read from</param>
            <returns>The Range transform</returns>
        </member>
        <member name="M:SVM.RangeTransform.Read(System.IO.Stream)">
            <summary>
            Reads a Range transform from a stream.
            </summary>
            <param name="stream">The stream to read from</param>
            <returns>The Range transform</returns>
        </member>
        <member name="T:SVM.Problem">
            <summary>
            Encapsulates a problem, or set of vectors which must be classified.
            </summary>
        </member>
        <member name="M:SVM.Problem.#ctor(System.Int32,System.Double[],SVM.Node[][],System.Int32)">
            <summary>
            Constructor.
            </summary>
            <param name="count">Number of vectors</param>
            <param name="y">The class labels</param>
            <param name="x">Vector data.</param>
            <param name="maxIndex">Maximum index for a vector</param>
        </member>
        <member name="M:SVM.Problem.#ctor">
            <summary>
            Empty Constructor.  Nothing is initialized.
            </summary>
        </member>
        <member name="M:SVM.Problem.Read(System.IO.Stream)">
            <summary>
            Reads a problem from a stream.
            </summary>
            <param name="stream">Stream to read from</param>
            <returns>The problem</returns>
        </member>
        <member name="M:SVM.Problem.Write(System.IO.Stream,SVM.Problem)">
            <summary>
            Writes a problem to a stream.
            </summary>
            <param name="stream">The stream to write the problem to.</param>
            <param name="problem">The problem to write.</param>
        </member>
        <member name="M:SVM.Problem.Read(System.String)">
            <summary>
            Reads a Problem from a file.
            </summary>
            <param name="filename">The file to read from.</param>
            <returns>the Probem</returns>
        </member>
        <member name="M:SVM.Problem.Write(System.String,SVM.Problem)">
            <summary>
            Writes a problem to a file.   This will overwrite any previous data in the file.
            </summary>
            <param name="filename">The file to write to</param>
            <param name="problem">The problem to write</param>
        </member>
        <member name="P:SVM.Problem.Count">
            <summary>
            Number of vectors.
            </summary>
        </member>
        <member name="P:SVM.Problem.Y">
            <summary>
            Class labels.
            </summary>
        </member>
        <member name="P:SVM.Problem.X">
            <summary>
            Vector data.
            </summary>
        </member>
        <member name="P:SVM.Problem.MaxIndex">
            <summary>
            Maximum index for a vector.
            </summary>
        </member>
        <member name="T:SVM.SvmType">
            <summary>
            Contains all of the types of SVM this library can model.
            </summary>
        </member>
        <member name="F:SVM.SvmType.C_SVC">
            <summary>
            C-SVC.
            </summary>
        </member>
        <member name="F:SVM.SvmType.NU_SVC">
            <summary>
            nu-SVC.
            </summary>
        </member>
        <member name="F:SVM.SvmType.ONE_CLASS">
            <summary>
            one-class SVM
            </summary>
        </member>
        <member name="F:SVM.SvmType.EPSILON_SVR">
            <summary>
            epsilon-SVR
            </summary>
        </member>
        <member name="F:SVM.SvmType.NU_SVR">
            <summary>
            nu-SVR
            </summary>
        </member>
        <member name="T:SVM.KernelType">
            <summary>
            Contains the various kernel types this library can use.
            </summary>
        </member>
        <member name="F:SVM.KernelType.LINEAR">
            <summary>
            Linear: u'*v
            </summary>
        </member>
        <member name="F:SVM.KernelType.POLY">
            <summary>
            Polynomial: (gamma*u'*v + coef0)^degree
            </summary>
        </member>
        <member name="F:SVM.KernelType.RBF">
            <summary>
            Radial basis function: exp(-gamma*|u-v|^2)
            </summary>
        </member>
        <member name="F:SVM.KernelType.SIGMOID">
            <summary>
            Sigmoid: tanh(gamma*u'*v + coef0)
            </summary>
        </member>
        <member name="F:SVM.KernelType.PRECOMPUTED">
            <summary>
            Precomputed kernel
            </summary>
        </member>
        <member name="T:SVM.Parameter">
            <summary>
            This class contains the various parameters which can affect the way in which an SVM
            is learned.  Unless you know what you are doing, chances are you are best off using
            the default values.
            </summary>
        </member>
        <member name="M:SVM.Parameter.#ctor">
            <summary>
            Default Constructor.  Gives good default values to all parameters.
            </summary>
        </member>
        <member name="M:SVM.Parameter.Clone">
            <summary>
            Creates a memberwise clone of this parameters object.
            </summary>
            <returns>The clone (as type Parameter)</returns>
        </member>
        <member name="P:SVM.Parameter.SvmType">
            <summary>
            Type of SVM (default C-SVC)
            </summary>
        </member>
        <member name="P:SVM.Parameter.KernelType">
            <summary>
            Type of kernel function (default Polynomial)
            </summary>
        </member>
        <member name="P:SVM.Parameter.Degree">