#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System.Collections.Generic;
using System.Linq;
namespace HeuristicLab.Problems.DataAnalysis.SupportVectorMachine {
public class SupportVectorMachineUtil {
///
/// Transforms into a data structure as needed by libSVM.
///
/// The problem data to transform
/// The index of the first row of to copy to the output.
/// The last of the first row of to copy to the output.
/// A problem data type that can be used to train a support vector machine.
public static SVM.Problem CreateSvmProblem(DataAnalysisProblemData problemData, int start, int end) {
int rowCount = end - start;
var targetVector = problemData.Dataset.GetVariableValues(problemData.TargetVariable.Value, start, end);
SVM.Node[][] nodes = new SVM.Node[targetVector.Length][];
List tempRow;
int maxNodeIndex = 0;
for (int row = 0; row < rowCount; row++) {
tempRow = new List();
foreach (var inputVariable in problemData.InputVariables.CheckedItems) {
int col = problemData.Dataset.GetVariableIndex(inputVariable.Value.Value);
double value = problemData.Dataset[start + row, col];
if (!double.IsNaN(value)) {
int nodeIndex = col + 1; // make sure the smallest nodeIndex = 1
tempRow.Add(new SVM.Node(nodeIndex, value));
if (nodeIndex > maxNodeIndex) maxNodeIndex = nodeIndex;
}
}
nodes[row] = tempRow.OrderBy(x => x.Index).ToArray(); // make sure the values are sorted by node index
}
return new SVM.Problem(targetVector.Length, targetVector, nodes, maxNodeIndex);
}
}
}