Changeset 13652

Timestamp:

03/05/16 19:41:24 (9 years ago)

Author:

gkronber

Message:

#2581:

• removed simplification of trees (temporarily for better debugging)
• renamed MaxSize parameter
• fixed a small bug in MCTS
• changed SymbolicExpressionGenerator to produce trees in the correct order

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression

Files:

• ExpressionEvaluator.cs (modified) (1 diff)
• MctsSymbolicRegressionAlgorithm.cs (modified) (3 diffs)
• MctsSymbolicRegressionStatic.cs (modified) (5 diffs)
• SymbolicExpressionGenerator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/ExpressionEvaluator.cs

@@ -183 +183 @@
 
                 var f = 1.0 / (maxFx * consts[curParamIdx]);
-                // adjust c so that maxFx*c = 1 TODO: this is not ideal as enforce positive argument to exp()
+                // adjust c so that maxFx*c = 1 TODO: this is not ideal as it enforces positive arguments to exp()
                 consts[curParamIdx] *= f;
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/MctsSymbolicRegressionAlgorithm.cs

@@ -70 +70 @@
       get { return (IFixedValueParameter<IntValue>)Parameters[IterationsParameterName]; }
     }
-    public IFixedValueParameter<IntValue> MaxSizeParameter {
+    public IFixedValueParameter<IntValue> MaxVariableReferencesParameter {
       get { return (IFixedValueParameter<IntValue>)Parameters[MaxVariablesParameterName]; }
     }
@@ -115 +115 @@
       set { SetSeedRandomlyParameter.Value.Value = value; }
     }
-    public int MaxSize {
-      get { return MaxSizeParameter.Value.Value; }
-      set { MaxSizeParameter.Value.Value = value; }
+    public int MaxVariableReferences {
+      get { return MaxVariableReferencesParameter.Value.Value; }
+      set { MaxVariableReferencesParameter.Value.Value = value; }
     }
     public double C {
@@ -244 +244 @@
       var problemData = (IRegressionProblemData)Problem.ProblemData.Clone();
       if (!AllowedFactors.CheckedItems.Any()) throw new ArgumentException("At least on type of factor must be allowed");
-      var state = MctsSymbolicRegressionStatic.CreateState(problemData, (uint)Seed, MaxSize, C, ScaleVariables, ConstantOptimizationIterations,
+      var state = MctsSymbolicRegressionStatic.CreateState(problemData, (uint)Seed, MaxVariableReferences, C, ScaleVariables, ConstantOptimizationIterations,
         lowerLimit, upperLimit,
         allowProdOfVars: AllowedFactors.CheckedItems.Any(s => s.Value.Value == VariableProductFactorName),

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/MctsSymbolicRegressionStatic.cs

@@ -175 +175 @@
           var treeGen = new SymbolicExpressionTreeGenerator(problemData.AllowedInputVariables.ToArray());
           var interpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
-          var simplifier = new SymbolicDataAnalysisExpressionTreeSimplifier();
 
           var t = new SymbolicExpressionTree(treeGen.Exec(bestCode, bestConsts, bestNParams, scalingFactor, scalingOffset));
-          var simpleT = simplifier.Simplify(t);
-          var model = new SymbolicRegressionModel(simpleT, interpreter, lowerEstimationLimit, upperEstimationLimit);
+          var model = new SymbolicRegressionModel(t, interpreter, lowerEstimationLimit, upperEstimationLimit);
 
           // model has already been scaled linearly in Eval
@@ -264 +262 @@
         alglib.minlmstate state;
         alglib.minlmreport rep = null;
-        alglib.minlmcreatevj(y.Length, optConsts, out state);
+        alglib.minlmcreatevj(y.Length, optConsts, out state);        
         alglib.minlmsetcond(state, 0.0, epsF, 0.0, nIters);
         //alglib.minlmsetgradientcheck(state, 0.000001);
@@ -281 +279 @@
 
       private void Func(double[] arg, double[] fi, object obj) {
-        // 0.5 * MSE and gradient
         var code = (byte[])obj;
         evaluator.Exec(code, x, arg, predBuf); // gradients are nParams x vLen
@@ -376 +373 @@
             tree.done = true;
             tree.children = null;
+            tree.visits = 1;
             return false;
           }
@@ -436 +434 @@
         }
       }
-      return bestChildrenBuf.Count > 0 ? bestChildrenBuf[rand.Next(bestChildrenBuf.Count)] : bestChildrenBuf[0];
+      return bestChildrenBuf[rand.Next(bestChildrenBuf.Count)];
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/SymbolicExpressionGenerator.cs

@@ -113 +113 @@
             break;
           case OpCodes.Add: {
-              var t1 = stack[topOfStack];
-              var t2 = stack[topOfStack - 1];
+              var t1 = stack[topOfStack - 1];
+              var t2 = stack[topOfStack];
               topOfStack--;
-              if (t2.Symbol is Addition) {
-                t2.AddSubtree(t1);
+              if (t1.Symbol is Addition) {
+                t1.AddSubtree(t2);
               } else {
                 var addNode = addSy.CreateTreeNode();
@@ -127 +127 @@
             }
           case OpCodes.Mul: {
-              var t1 = stack[topOfStack];
-              var t2 = stack[topOfStack - 1];
+              var t1 = stack[topOfStack - 1];
+              var t2 = stack[topOfStack];
               topOfStack--;
-              if (t2.Symbol is Multiplication) {
-                t2.AddSubtree(t1);
+              if (t1.Symbol is Multiplication) {
+                t1.AddSubtree(t2);
               } else {
                 var mulNode = mulSy.CreateTreeNode();