00001 package libsvm; 00002 public class svm_parameter implements Cloneable,java.io.Serializable 00003 { 00004 /* svm_type */ 00005 public static final int C_SVC = 0; 00006 public static final int NU_SVC = 1; 00007 public static final int ONE_CLASS = 2; 00008 public static final int EPSILON_SVR = 3; 00009 public static final int NU_SVR = 4; 00010 00011 /* kernel_type */ 00012 public static final int LINEAR = 0; 00013 public static final int POLY = 1; 00014 public static final int RBF = 2; 00015 public static final int SIGMOID = 3; 00016 public static final int PRECOMPUTED = 4; 00017 00018 public int svm_type; 00019 public int kernel_type; 00020 public int degree; // for poly 00021 public double gamma; // for poly/rbf/sigmoid 00022 public double coef0; // for poly/sigmoid 00023 00024 // these are for training only 00025 public double cache_size; // in MB 00026 public double eps; // stopping criteria 00027 public double C; // for C_SVC, EPSILON_SVR and NU_SVR 00028 public int nr_weight; // for C_SVC 00029 public int[] weight_label; // for C_SVC 00030 public double[] weight; // for C_SVC 00031 public double nu; // for NU_SVC, ONE_CLASS, and NU_SVR 00032 public double p; // for EPSILON_SVR 00033 public int shrinking; // use the shrinking heuristics 00034 public int probability; // do probability estimates 00035 00036 public Object clone() 00037 { 00038 try 00039 { 00040 return super.clone(); 00041 } catch (CloneNotSupportedException e) 00042 { 00043 return null; 00044 } 00045 } 00046 00047 }