diff --git a/lang/fr/gklearn/gedlib/lib/libsvm.3.22/java/libsvm/svm_parameter.java b/lang/fr/gklearn/gedlib/lib/libsvm.3.22/java/libsvm/svm_parameter.java
new file mode 100644
index 0000000..429f041
--- /dev/null
+++ b/lang/fr/gklearn/gedlib/lib/libsvm.3.22/java/libsvm/svm_parameter.java
@@ -0,0 +1,47 @@
+package 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;
+		}
+	}
+
+}