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source: branches/ExcelIntegration/HeuristicLabExcel/ExcelFunctions.cs @ 11594

Last change on this file since 11594 was 11217, checked in by gkronber, 10 years ago

initial commit of demo of excel interoperability (PredictRandomForest)

File size: 2.1 KB
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[11217]1using System;
2using System.Collections.Generic;
3using System.Linq;
4using ExcelDna.Integration;
5using HeuristicLab.Problems.DataAnalysis;
6
7namespace HeuristicLabExcel {
8
9  public class ExcelFunctions {
10    /* Standard example from ExcelDNA */
11    [ExcelFunction(Description = "Multiplies two numbers", Category = "Useful functions")]
12    public static double MultiplyThem(double x, double y) {
13      return x * y;
14    }
15    [ExcelFunction(Description = "Random forest", Category = "Useful functions")]
16    public static double[,] PredictRandomForest(double[,] x, double[] y) {
17      int nRows = x.GetLength(0);
18      int nCols = x.GetLength(1);
19      if (nRows > 5000) throw new ArgumentException("y");
20      if (nCols >= nRows) throw new ArgumentException("x");
21      var inputs = Enumerable.Range(0, nCols).Select(i => "x" + i);
22      var target = "y";
23      var variables = inputs.Concat(new string[] { target });
24      // copy data
25      var xy = new double[nRows, nCols + 1];
26      for (int r = 0; r < nRows; r++) {
27        for (int c = 0; c < nCols; c++) {
28          xy[r, c] = x[r, c];
29        }
30        if (r < y.Length)
31          xy[r, nCols] = y[r];
32      }
33      var ds = new Dataset(variables, xy);
34
35      var problemData = new RegressionProblemData(ds, inputs, target);
36      problemData.TrainingPartition.Start = 0;
37      problemData.TrainingPartition.End = y.Length;
38      problemData.TestPartition.Start = y.Length;
39      problemData.TestPartition.End = nRows;
40
41      double rmsError;
42      double oobAvgRelError;
43      double oobRmsError;
44      double avgRelError;
45      var rf = HeuristicLab.Algorithms.DataAnalysis.RandomForestRegression.CreateRandomForestRegressionSolution(problemData, 100, 0.5, 0.5, 31415, out rmsError, out avgRelError, out oobRmsError, out oobAvgRelError);
46
47      // copy for output
48      var res = new double[nRows, 1];
49      var estValuesEnum = rf.EstimatedValues.GetEnumerator();
50      estValuesEnum.MoveNext();
51      for (int r = 0; r < nRows; r++) {
52        res[r, 0] = estValuesEnum.Current;
53        estValuesEnum.MoveNext();
54      }
55      return res;
56    }
57  }
58}
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