Changeset 11571 for branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Timestamp:

11/24/14 15:16:59 (10 years ago)

Author:

bburlacu

Message:

#2276: Commit initial version of IDataset interface and code refactoring.

Location:

branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Files:

• ClassificationEnsembleModel.cs (modified) (2 diffs)
• ClassificationEnsembleSolution.cs (modified) (1 diff)
• ClassificationProblemData.cs (modified) (2 diffs)
• DiscriminantFunctionClassificationModel.cs (modified) (1 diff)

branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationEnsembleModel.cs

@@ -67 +67 @@
     }
 
-    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(IDataset dataset, IEnumerable<int> rows) {
       var estimatedValuesEnumerators = (from model in models
                                         select model.GetEstimatedClassValues(dataset, rows).GetEnumerator())
@@ -82 +82 @@
     #region IClassificationModel Members
 
-    public IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
       foreach (var estimatedValuesVector in GetEstimatedClassValueVectors(dataset, rows)) {
         // return the class which is most often occuring

branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationEnsembleSolution.cs

@@ -231 +231 @@
     }
 
-    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(IDataset dataset, IEnumerable<int> rows) {
       if (!Model.Models.Any()) yield break;
       var estimatedValuesEnumerators = (from model in Model.Models

branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationProblemData.cs

@@ -300 +300 @@
     }
 
-    public ClassificationProblemData(Dataset dataset, IEnumerable<string> allowedInputVariables, string targetVariable, IEnumerable<ITransformation> transformations = null)
+    public ClassificationProblemData(IDataset dataset, IEnumerable<string> allowedInputVariables, string targetVariable, IEnumerable<ITransformation> transformations = null)
       : base(dataset, allowedInputVariables, transformations ?? Enumerable.Empty<ITransformation>()) {
       var validTargetVariableValues = CheckVariablesForPossibleTargetVariables(dataset).Select(x => new StringValue(x).AsReadOnly()).ToList();
@@ -313 +313 @@
     }
 
-    public static IEnumerable<string> CheckVariablesForPossibleTargetVariables(Dataset dataset) {
+    public static IEnumerable<string> CheckVariablesForPossibleTargetVariables(IDataset dataset) {
       int maxSamples = Math.Min(InspectedRowsToDetermineTargets, dataset.Rows);
       var validTargetVariables = (from v in dataset.DoubleVariables

branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationModel.cs

@@ -111 +111 @@
 
 
-    public IEnumerable<double> GetEstimatedValues(Dataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
       return model.GetEstimatedValues(dataset, rows);
     }
 
-    public IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
       if (!Thresholds.Any() && !ClassValues.Any()) throw new ArgumentException("No thresholds and class values were set for the current classification model.");
       foreach (var x in GetEstimatedValues(dataset, rows)) {