Changeset 14869 for branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

Timestamp:

04/14/17 08:58:45 (7 years ago)

Author:

gkronber

Message:

#2699: merged changesets from trunk to branch

Location:

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• . (modified) (1 prop)
• Linear/MultinomialLogitClassification.cs (modified) (4 diffs)

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

@@ -23 +23 @@
 using System.Collections.Generic;
 using System.Linq;
+using System.Threading;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -57 +58 @@
 
     #region logit classification
-    protected override void Run() {
+    protected override void Run(CancellationToken cancellationToken) {
       double rmsError, relClassError;
       var solution = CreateLogitClassificationSolution(Problem.ProblemData, out rmsError, out relClassError);
@@ -68 +69 @@
       var dataset = problemData.Dataset;
       string targetVariable = problemData.TargetVariable;
-      IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
+      var doubleVariableNames = problemData.AllowedInputVariables.Where(dataset.VariableHasType<double>);
+      var factorVariableNames = problemData.AllowedInputVariables.Where(dataset.VariableHasType<string>);
       IEnumerable<int> rows = problemData.TrainingIndices;
-      double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
+      double[,] inputMatrix = dataset.ToArray(doubleVariableNames.Concat(new string[] { targetVariable }), rows);
+
+      var factorVariableValues = dataset.GetFactorVariableValues(factorVariableNames, rows);
+      var factorMatrix = dataset.ToArray(factorVariableValues, rows);
+      inputMatrix = factorMatrix.HorzCat(inputMatrix);
+
       if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
         throw new NotSupportedException("Multinomial logit classification does not support NaN or infinity values in the input dataset.");
@@ -95 +102 @@
       relClassError = alglib.mnlrelclserror(lm, inputMatrix, nRows);
 
-      MultinomialLogitClassificationSolution solution = new MultinomialLogitClassificationSolution(new MultinomialLogitModel(lm, targetVariable, allowedInputVariables, classValues), (IClassificationProblemData)problemData.Clone());
+      MultinomialLogitClassificationSolution solution = new MultinomialLogitClassificationSolution(new MultinomialLogitModel(lm, targetVariable, doubleVariableNames, factorVariableValues, classValues), (IClassificationProblemData)problemData.Clone());
       return solution;
     }