Changeset 17489 for branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4

Timestamp:

04/01/20 15:49:03 (5 years ago)

Author:

pfleck

Message:

#3040 Added version with explicit array shapes for explicit broadcasting.

File:

• branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4/InteractiveSymbolicRegressionSolutionSimplifierView.cs (modified) (2 diffs)

branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4/InteractiveSymbolicRegressionSolutionSimplifierView.cs

@@ -43 +43 @@
 
       var tree = Content?.Model?.SymbolicExpressionTree;
-      btnOptimizeConstants.Enabled = tree != null && NonlinearLeastSquaresConstantOptimizationEvaluator.CanOptimizeConstants(tree);
+      //btnOptimizeConstants.Enabled = tree != null && NonlinearLeastSquaresConstantOptimizationEvaluator.CanOptimizeConstants(tree);
+      btnOptimizeConstants.Enabled = tree != null && TensorFlowConstantOptimizationEvaluator.CanOptimizeConstants(tree);
     }
 
@@ -65 +66 @@
       do {
         prevResult = result;
-        tree = NonlinearLeastSquaresConstantOptimizationEvaluator.OptimizeTree(tree, regressionProblemData, regressionProblemData.TrainingIndices,
-          applyLinearScaling: true, maxIterations: constOptIterations, updateVariableWeights: true,
-          cancellationToken: cancellationToken, iterationCallback: (args, func, obj) => {
-            double newProgressValue = progress.ProgressValue + (1.0 / (constOptIterations + 2) / maxRepetitions); // (constOptIterations + 2) iterations are reported
-            progress.ProgressValue = Math.Min(newProgressValue, 1.0);
-          });
+        //tree = NonlinearLeastSquaresConstantOptimizationEvaluator.OptimizeTree(tree, regressionProblemData, regressionProblemData.TrainingIndices,
+        //  applyLinearScaling: true, maxIterations: constOptIterations, updateVariableWeights: true,
+        //  cancellationToken: cancellationToken, iterationCallback: (args, func, obj) => {
+        //    double newProgressValue = progress.ProgressValue + (1.0 / (constOptIterations + 2) / maxRepetitions); // (constOptIterations + 2) iterations are reported
+        //    progress.ProgressValue = Math.Min(newProgressValue, 1.0);
+        //  });
+        tree = TensorFlowConstantOptimizationEvaluator.OptimizeTree(tree, regressionProblemData, regressionProblemData.TrainingIndices,
+          applyLinearScaling: true, updateVariableWeights: true, maxIterations: 10, learningRate: 0.001);
         result = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(model.Interpreter, tree,
           model.LowerEstimationLimit, model.UpperEstimationLimit, regressionProblemData, regressionProblemData.TrainingIndices, applyLinearScaling: true);