Changeset 15406 for stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators
- Timestamp:
- 10/06/17 13:38:16 (7 years ago)
- Location:
- stable
- Files:
-
- 4 edited
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- Unmodified
- Added
- Removed
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stable
- Property svn:mergeinfo changed
/trunk/sources merged: 15371-15372,15390,15400,15402
- Property svn:mergeinfo changed
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stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression
- Property svn:mergeinfo changed
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stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4
- Property svn:mergeinfo changed
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stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs
r15142 r15406 156 156 int maxIterations, bool updateVariableWeights = true, 157 157 double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue, 158 bool updateConstantsInTree = true ) {158 bool updateConstantsInTree = true, Action<double[], double, object> iterationCallback = null) { 159 159 160 160 // numeric constants in the tree become variables for constant opt … … 210 210 alglib.ndimensional_pfunc function_cx_1_func = CreatePFunc(func); 211 211 alglib.ndimensional_pgrad function_cx_1_grad = CreatePGrad(func_grad); 212 alglib.ndimensional_rep xrep = (p, f, obj) => iterationCallback(p, f, obj); 212 213 213 214 try { 214 215 alglib.lsfitcreatefg(x, y, c, n, m, k, false, out state); 215 216 alglib.lsfitsetcond(state, 0.0, 0.0, maxIterations); 217 alglib.lsfitsetxrep(state, iterationCallback != null); 216 218 //alglib.lsfitsetgradientcheck(state, 0.001); 217 alglib.lsfitfit(state, function_cx_1_func, function_cx_1_grad, null, null);219 alglib.lsfitfit(state, function_cx_1_func, function_cx_1_grad, xrep, null); 218 220 alglib.lsfitresults(state, out retVal, out c, out rep); 219 221 }
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