public static SVMProblem Convert(svm_problem x) { double[] y_array = new double[x.l]; Marshal.Copy(x.y, y_array, 0, y_array.Length); List <SVMNode[]> x_array = new List <SVMNode[]>(); IntPtr i_ptr_x = x.x; for (int i = 0; i < x.l; i++) { IntPtr ptr_nodes = (IntPtr)Marshal.PtrToStructure(i_ptr_x, typeof(IntPtr)); SVMNode[] nodes = SVMNode.Convert(ptr_nodes); x_array.Add(nodes); i_ptr_x = IntPtr.Add(i_ptr_x, Marshal.SizeOf(typeof(IntPtr))); } SVMProblem y = new SVMProblem(); for (int i = 0; i < x.l; i++) { y.Add(x_array[i], y_array[i]); } return(y); }
public OneClassClassifier(List<SVMNode[]> trainingData) { SVMProblem problem = new SVMProblem(); for (int i = 0; i < trainingData.Count; i++) { problem.Add(trainingData[i], 1); } _trainingData = problem; }
public SVMProblem Clone() { SVMProblem y = new SVMProblem(); for (int i = 0; i < Length; i++) { SVMNode[] nodes = X[i].Select(x => x.Clone()).ToArray(); y.Add(nodes, Y[i]); } return y; }
public SVMProblem Clone() { SVMProblem y = new SVMProblem(); for (int i = 0; i < Length; i++) { SVMNode[] nodes = X[i].Select(x => x.Clone()).ToArray(); y.Add(nodes, Y[i]); } return(y); }
public static SVMProblem Convert(svm_problem x) { double[] y_array = new double[x.l]; Marshal.Copy(x.y, y_array, 0, y_array.Length); List<SVMNode[]> x_array = new List<SVMNode[]>(); IntPtr i_ptr_x = x.x; for (int i = 0; i < x.l; i++) { IntPtr ptr_nodes = (IntPtr)Marshal.PtrToStructure(i_ptr_x, typeof(IntPtr)); SVMNode[] nodes = SVMNode.Convert(ptr_nodes); x_array.Add(nodes); i_ptr_x = IntPtr.Add(i_ptr_x, Marshal.SizeOf(typeof(IntPtr))); } SVMProblem y = new SVMProblem(); for (int i = 0; i < x.l; i++) { y.Add(x_array[i], y_array[i]); } return y; }