content: package org.machinelearning.svm.libsvm;
  public class svm_parameter implements Cloneable,java.io.Serializable
  {
  	/* svm_type */
  	public static final int C_SVC = 0;
  	public static final int NU_SVC = 1;
  	public static final int ONE_CLASS = 2;
  	public static final int EPSILON_SVR = 3;
  	public static final int NU_SVR = 4;
  
  	/* kernel_type */
  	public static final int LINEAR = 0;
  	public static final int POLY = 1;
  	public static final int RBF = 2;
  	public static final int SIGMOID = 3;
  	public static final int PRECOMPUTED = 4;
  
  	public int svm_type;
  	public int kernel_type;
  	public int degree;	// for poly
  	public double gamma;	// for poly/rbf/sigmoid
  	public double coef0;	// for poly/sigmoid
  
  	// these are for training only
  	public double cache_size; // in MB
  	public double eps;	// stopping criteria
  	public double C;	// for C_SVC, EPSILON_SVR and NU_SVR
  	public int nr_weight;		// for C_SVC
  	public int[] weight_label;	// for C_SVC
  	public double[] weight;		// for C_SVC
  	public double nu;	// for NU_SVC, ONE_CLASS, and NU_SVR
  	public double p;	// for EPSILON_SVR
  	public int shrinking;	// use the shrinking heuristics
  	public int probability; // do probability estimates
  
  	public Object clone()
  	{
  		try
  		{
  			return super.clone();
  		} catch (CloneNotSupportedException e)
  		{
  			return null;
  		}
  	}
  
  }
  