Package gov.nih.mipav.view.renderer.WildMagic.ProstateFramework.liblinearsvm

Class Model

  • All Implemented Interfaces:
    java.io.Serializable
    public final class Model
extends java.lang.Object
implements java.io.Serializable
    Copyright (c) 2007-2014 The LIBLINEAR Project. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

    Model stores the model obtained from the training procedure

    use Linear#loadModel(String) and Linear#saveModel(String, Model) to load/save it

    See Also:
    Serialized Form

    • Field Detail

      • bias

        double bias

      • label

        int[] label
        label of each class

      • nr_class

        int nr_class

      • nr_feature

        int nr_feature

      • w

        double[] w
        feature weight array

    • Constructor Detail

      • Model

        public Model()

    • Method Detail

      • getNrClass

        public int getNrClass()
        Returns:
        number of classes

      • getNrFeature

        public int getNrFeature()
        Returns:
        number of features

      • getLabels

        public int[] getLabels()

      • getFeatureWeights

        public double[] getFeatureWeights()
        The nr_feature*nr_class array w gives feature weights. We use one against the rest for multi-class classification, so each feature index corresponds to nr_class weight values. Weights are organized in the following way 
         +------------------+------------------+------------+
 | nr_class weights | nr_class weights |  ...
 | for 1st feature  | for 2nd feature  |
 +------------------+------------------+------------+
        If bias >= 0, x becomes [x; bias]. The number of features is increased by one, so w is a (nr_feature+1)*nr_class array. The value of bias is stored in the variable bias.
        Returns:
        a copy of the feature weight array as described
        See Also:
        getBias()

      • toString

        public java.lang.String toString()
        Overrides:
        toString in class java.lang.Object

      • hashCode

        public int hashCode()
        Overrides:
        hashCode in class java.lang.Object

      • equals

        public boolean equals​(java.lang.Object obj)
        Overrides:
        equals in class java.lang.Object

      • equals

        protected static boolean equals​(double[] a,
                                double[] a2)
        don't use Arrays.equals(double[], double[]) here, cause 0.0 and -0.0 should be handled the same
        See Also:
        Linear.saveModel(java.io.Writer, Model)

      • load

        public static Model load​(java.io.File file)
                  throws java.io.IOException
        see Linear.loadModel(File)
        Throws:
        java.io.IOException

      • load

        public static Model load​(java.io.Reader inputReader)
                  throws java.io.IOException
        see Linear.loadModel(Reader)
        Throws:
        java.io.IOException