package libsvm;public class svm_parameter{	/* 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 int svm_type;	public int kernel_type;	public double 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}