Changeset 14345 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/SymbolicDataAnalysisExpressionTreeInterpreter.cs

Timestamp:

10/21/16 17:59:36 (7 years ago)

Author:

gkronber

Message:

#2690: implemented methods to generate symbolic expression tree solutions for decision tree models (random forest and gradient boosted) as well as views which make it possible to inspect each of the individual trees in a GBT and RF solution

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/SymbolicDataAnalysisExpressionTreeInterpreter.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/SymbolicDataAnalysisExpressionTreeInterpreter.cs

@@ -471 +471 @@
             if (row < 0 || row >= dataset.Rows) return double.NaN;
             var variableConditionTreeNode = (VariableConditionTreeNode)currentInstr.dynamicNode;
-            double variableValue = ((IList<double>)currentInstr.data)[row];
-            double x = variableValue - variableConditionTreeNode.Threshold;
-            double p = 1 / (1 + Math.Exp(-variableConditionTreeNode.Slope * x));
-
-            double trueBranch = Evaluate(dataset, ref row, state);
-            double falseBranch = Evaluate(dataset, ref row, state);
-
-            return trueBranch * p + falseBranch * (1 - p);
+            if (!variableConditionTreeNode.Symbol.IgnoreSlope) {
+              double variableValue = ((IList<double>)currentInstr.data)[row];
+              double x = variableValue - variableConditionTreeNode.Threshold;
+              double p = 1 / (1 + Math.Exp(-variableConditionTreeNode.Slope * x));
+
+              double trueBranch = Evaluate(dataset, ref row, state);
+              double falseBranch = Evaluate(dataset, ref row, state);
+
+              return trueBranch * p + falseBranch * (1 - p);
+            } else {
+              // strict threshold
+              double variableValue = ((IList<double>)currentInstr.data)[row];
+              if (variableValue <= variableConditionTreeNode.Threshold) {
+                var left = Evaluate(dataset, ref row, state);
+                state.SkipInstructions();
+                return left;
+              } else {
+                state.SkipInstructions();
+                return Evaluate(dataset, ref row, state);
+              }
+            }
           }
         default: