- Timestamp:
- 07/06/17 10:19:37 (7 years ago)
- Location:
- stable
- Files:
-
- 3 edited
Legend:
- Unmodified
- Added
- Removed
-
stable
- Property svn:mergeinfo changed
-
stable/HeuristicLab.Algorithms.DataAnalysis
-
stable/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitModel.cs
r14186 r15131 56 56 [Storable] 57 57 private double[] classValues; 58 [Storable] 59 private List<KeyValuePair<string, IEnumerable<string>>> factorVariables; 60 58 61 [StorableConstructor] 59 62 private MultinomialLogitModel(bool deserializing) … … 68 71 allowedInputVariables = (string[])original.allowedInputVariables.Clone(); 69 72 classValues = (double[])original.classValues.Clone(); 73 this.factorVariables = original.factorVariables.Select(kvp => new KeyValuePair<string, IEnumerable<string>>(kvp.Key, new List<string>(kvp.Value))).ToList(); 70 74 } 71 public MultinomialLogitModel(alglib.logitmodel logitModel, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues)75 public MultinomialLogitModel(alglib.logitmodel logitModel, string targetVariable, IEnumerable<string> doubleInputVariables, IEnumerable<KeyValuePair<string, IEnumerable<string>>> factorVariables, double[] classValues) 72 76 : base(targetVariable) { 73 77 this.name = ItemName; 74 78 this.description = ItemDescription; 75 79 this.logitModel = logitModel; 76 this.allowedInputVariables = allowedInputVariables.ToArray(); 80 this.allowedInputVariables = doubleInputVariables.ToArray(); 81 this.factorVariables = factorVariables.Select(kvp => new KeyValuePair<string, IEnumerable<string>>(kvp.Key, new List<string>(kvp.Value))).ToList(); 77 82 this.classValues = (double[])classValues.Clone(); 83 } 84 85 [StorableHook(HookType.AfterDeserialization)] 86 private void AfterDeserialization() { 87 // BackwardsCompatibility3.3 88 #region Backwards compatible code, remove with 3.4 89 factorVariables = new List<KeyValuePair<string, IEnumerable<string>>>(); 90 #endregion 78 91 } 79 92 … … 83 96 84 97 public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) { 98 85 99 double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables, rows); 100 double[,] factorData = AlglibUtil.PrepareInputMatrix(dataset, factorVariables, rows); 101 102 inputData = factorData.HorzCat(inputData); 86 103 87 104 int n = inputData.GetLength(0);
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