Changeset 9499 for branches/sluengo/HeuristicLab.Problems.TradeRules/Solution

Timestamp:

05/19/13 11:47:34 (11 years ago)

Author:

sluengo

Message:

 

File:

• branches/sluengo/HeuristicLab.Problems.TradeRules/Solution/TradeRulesSolutionBase.cs (modified) (6 diffs)

branches/sluengo/HeuristicLab.Problems.TradeRules/Solution/TradeRulesSolutionBase.cs

@@ -9 +9 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
+using HeuristicLab.Problems.TradeRules.Evaluator;
 
 namespace HeuristicLab.Problems.TradeRules
@@ -17 +18 @@
         private const string TrainingCashResultName = "Cash after the operation (training)";
         private const string TestCashResultName = "Cash after the operation (test)";
+        private const string TrainingUpDaysResultName = "Number of days that stock market goes up (training)";
+        private const string TrainingDownDaysResultName = "Number of days that stock market goes down (training)";
+        private const string TrainingHeuristicResultName = "Percentage of right actions after the operation (training)";
+        private const string TestHeuristicResultName = "Percentage of right actions after the operation (test)";
         private const string TrainingMeanSquaredErrorResultName = "Mean squared error (training)";
         private const string TestMeanSquaredErrorResultName = "Mean squared error (test)";
@@ -63 +68 @@
             private set { ((DoubleValue)this[TestCashResultName].Value).Value = value; }
         }
+
+        public double TrainingHeuristic
+        {
+            get { return ((DoubleValue)this[TrainingHeuristicResultName].Value).Value; }
+            private set { ((DoubleValue)this[TrainingHeuristicResultName].Value).Value = value; }
+        }
+        public double TestHeuristic
+        {
+            get { return ((DoubleValue)this[TestHeuristicResultName].Value).Value; }
+            private set { ((DoubleValue)this[TestHeuristicResultName].Value).Value = value; }
+        }
+
+        public double NumberUpDays
+        {
+            get { return ((DoubleValue)this[TrainingUpDaysResultName].Value).Value; }
+            private set { ((DoubleValue)this[TrainingUpDaysResultName].Value).Value = value; }
+        }
+
+        public double NumberDownDays
+        {
+            get { return ((DoubleValue)this[TrainingDownDaysResultName].Value).Value; }
+            private set { ((DoubleValue)this[TrainingDownDaysResultName].Value).Value = value; }
+        }
+
         public double TradeDays
         {
@@ -78 +107 @@
             private set { ((DoubleValue)this[TestTotalTradesResultName].Value).Value = value; }
         }
-        public double TrainingMeanSquaredError
+       public double TrainingMeanSquaredError
         {
             get { return ((DoubleValue)this[TrainingMeanSquaredErrorResultName].Value).Value; }
@@ -148 +177 @@
     protected TradeRulesSolutionBase(IRegressionModel model, IRegressionProblemData problemData)
       : base(model, problemData) {
-      Add(new Result(TrainingCashResultName, "Cash obtained after training period in the stock market", new DoubleValue()));
+      /*Add(new Result(TrainingCashResultName, "Cash obtained after training period in the stock market", new DoubleValue()));*/
       Add(new Result(TestCashResultName, "Cash obtained after test period in the stock market", new DoubleValue()));
+      Add(new Result(TrainingHeuristicResultName, "Percentage of right actions after training period in the stock market", new DoubleValue()));
+      Add(new Result(TestHeuristicResultName, "Percentage of right actions after test period in the stock market", new DoubleValue()));
+      Add(new Result(TrainingUpDaysResultName, "Number of days actions go up in the stock market", new DoubleValue()));
+      Add(new Result(TrainingDownDaysResultName, "Number of days actions down up in the stock market", new DoubleValue()));
+     
       Add(new Result(TestTradeDaysResultName, "Number of trading days", new DoubleValue()));
       Add(new Result(TestNumberTradesResultName, "Number of trades", new DoubleValue()));
       Add(new Result(TestTotalTradesResultName, "Total trades", new DoubleValue()));
      }
-
-    [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserialization()
-    {
-        // BackwardsCompatibility3.4
-
-        #region Backwards compatible code, remove with 3.5
-
-        if (!ContainsKey(TrainingMeanAbsoluteErrorResultName))
-        {
-            OnlineCalculatorError errorState;
-            Add(new Result(TrainingMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the training partition", new DoubleValue()));
-            double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
-            TrainingMeanAbsoluteError = errorState == OnlineCalculatorError.None ? trainingMAE : double.NaN;
-        }
-
-        if (!ContainsKey(TestMeanAbsoluteErrorResultName))
-        {
-            OnlineCalculatorError errorState;
-            Add(new Result(TestMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the test partition", new DoubleValue()));
-            double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
-            TestMeanAbsoluteError = errorState == OnlineCalculatorError.None ? testMAE : double.NaN;
-        }
-
-        if (!ContainsKey(TrainingMeanErrorResultName))
-        {
-            OnlineCalculatorError errorState;
-            Add(new Result(TrainingMeanErrorResultName, "Mean of errors of the model on the training partition", new DoubleValue()));
-            double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
-            TrainingMeanError = errorState == OnlineCalculatorError.None ? trainingME : double.NaN;
-        }
-        if (!ContainsKey(TestMeanErrorResultName))
-        {
-            OnlineCalculatorError errorState;
-            Add(new Result(TestMeanErrorResultName, "Mean of errors of the model on the test partition", new DoubleValue()));
-            double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
-            TestMeanError = errorState == OnlineCalculatorError.None ? testME : double.NaN;
-        }
-        #endregion
-    }
-
-
     protected void CalculateResults()
     {
@@ -203 +195 @@
         IEnumerable<double> estimatedTestValues = EstimatedTestValues; // cache values
         IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);
-
-        double trainingCTR = OnlineTradeRulesCalculator.Calculate(estimatedTrainingValues, ProblemData, ProblemData.TrainingIndices);
-        TrainingCash = trainingCTR;
+   
+        /*double trainingCTR = OnlineTradeRulesCalculator.Calculate(estimatedTrainingValues, ProblemData, ProblemData.TrainingIndices);
+        TrainingCash = trainingCTR;*/
+
+        double trainingHTR = OnlineHeuristicTradeRulesCalculator.Calculate(estimatedTrainingValues, ProblemData, ProblemData.TrainingIndices);
+        TrainingHeuristic = trainingHTR;
+        double trainingUpDays = OnlineHeuristicTradeRulesCalculator.getNumberUpDays();
+        NumberUpDays = trainingUpDays;
+        double trainingDownDays = OnlineHeuristicTradeRulesCalculator.getNumberDownDays();
+        NumberDownDays = trainingDownDays;
+
+        double testHTR = OnlineHeuristicTradeRulesCalculator.Calculate(estimatedTestValues, ProblemData, ProblemData.TestIndices);
+        TestHeuristic = testHTR;
+
         double testCTR = OnlineTradeRulesCalculator.Calculate(estimatedTestValues, ProblemData, ProblemData.TestIndices);
         TestCash = testCTR;