Changeset 16449

Timestamp:

12/23/18 09:16:37 (5 years ago)

Author:

gkronber

Message:

#2892: added a view for LR models with prediction intervals

Location:

trunk

Files:

• HeuristicLab.Algorithms.DataAnalysis.Views/3.4/HeuristicLab.Algorithms.DataAnalysis.Views-3.4.csproj (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis.Views/3.4/LinearRegressionModelView.Designer.cs (added)
• HeuristicLab.Algorithms.DataAnalysis.Views/3.4/LinearRegressionModelView.cs (added)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegressionModel.cs (modified) (7 diffs)

trunk/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/HeuristicLab.Algorithms.DataAnalysis.Views-3.4.csproj

@@ -142 +142 @@
     <Compile Include="OneFactorClassificationModelView.Designer.cs">
       <DependentUpon>OneFactorClassificationModelView.cs</DependentUpon>
+    </Compile>
+    <Compile Include="LinearRegressionModelView.cs">
+      <SubType>UserControl</SubType>
+    </Compile>
+    <Compile Include="LinearRegressionModelView.Designer.cs">
+      <DependentUpon>LinearRegressionModelView.cs</DependentUpon>
     </Compile>
     <Compile Include="RandomForestModelView.cs">

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegressionModel.cs

@@ -22 +22 @@
 using System;
 using System.Collections.Generic;
+using System.Drawing;
 using System.Linq;
 using HeuristicLab.Common;
@@ -35 +36 @@
   [Item("Linear Regression Model", "Represents a linear regression model.")]
   public sealed class LinearRegressionModel : RegressionModel, IConfidenceRegressionModel {
+    public static new Image StaticItemImage {
+      get { return HeuristicLab.Common.Resources.VSImageLibrary.Function; }
+    }
 
     [Storable]
@@ -51 +55 @@
 
     public override IEnumerable<string> VariablesUsedForPrediction {
-      get { return allowedInputVariables.Union(factorVariables.Select(f => f.Key)); }
+      get { return doubleVariables.Union(factorVariables.Select(f => f.Key)); }
     }
 
     [Storable]
-    private string[] allowedInputVariables;
+    private string[] doubleVariables;
     [Storable]
     private List<KeyValuePair<string, IEnumerable<string>>> factorVariables;
+
+    /// <summary>
+    /// Enumerable of variable names used by the model including one-hot-encoded of factor variables.
+    /// </summary>
+    public IEnumerable<string> ParameterNames {
+      get {
+        return factorVariables.SelectMany(kvp => kvp.Value.Select(factorVal => $"{kvp.Key}={factorVal}"))
+          .Concat(doubleVariables)
+          .Concat(new[] { "<const>" });
+      }
+    }
 
     [StorableConstructor]
@@ -69 +84 @@
       this.NoiseSigma = original.NoiseSigma;
 
-      allowedInputVariables = (string[])original.allowedInputVariables.Clone();
+      doubleVariables = (string[])original.doubleVariables.Clone();
       this.factorVariables = original.factorVariables.Select(kvp => new KeyValuePair<string, IEnumerable<string>>(kvp.Key, new List<string>(kvp.Value))).ToList();
     }
@@ -81 +96 @@
       Array.Copy(covariance, C, covariance.Length);
       this.NoiseSigma = noiseSigma;
-      var stringInputVariables = factorVariables.Select(f => f.Key).Distinct();
-      this.allowedInputVariables = doubleInputVariables.ToArray();
+      this.doubleVariables = doubleInputVariables.ToArray();
+      // clone
       this.factorVariables = factorVariables.Select(kvp => new KeyValuePair<string, IEnumerable<string>>(kvp.Key, new List<string>(kvp.Value))).ToList();
     }
@@ -95 +110 @@
 
     public override IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
-      double[,] inputData = dataset.ToArray(allowedInputVariables, rows);
+      double[,] inputData = dataset.ToArray(doubleVariables, rows);
       double[,] factorData = dataset.ToArray(factorVariables, rows);
 
@@ -114 +129 @@
 
     public IEnumerable<double> GetEstimatedVariances(IDataset dataset, IEnumerable<int> rows) {
-      double[,] inputData = dataset.ToArray(allowedInputVariables, rows);
+      double[,] inputData = dataset.ToArray(doubleVariables, rows);
       double[,] factorData = dataset.ToArray(factorVariables, rows);