german with cost matrix

lambda/src/LambdaDatasets/GermanDataset.hs

@@ -38,7 +38,7 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(Int -> Int -> Int))), ["(+)", "(-)", "(*)"]),
             -- Logic
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Bool -> Bool))), ["(&&)", "(||)"]),
-            -- Ordered Enums
+            -- Ordered
             ((Ref.SomeTypeRep (Ref.TypeRep @(Int -> Int -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(AccountStatus -> AccountStatus -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(CreditHistory -> CreditHistory -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
@@ -46,7 +46,7 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(EmploymentStatus -> EmploymentStatus -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(OtherDebtors -> OtherDebtors -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Job -> Job -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
-            -- Eq Enum
+            -- Eq
             ((Ref.SomeTypeRep (Ref.TypeRep @(GermanClass -> GermanClass -> Bool))), ["(==)", "(/=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Purpose -> Purpose -> Bool))), ["(==)", "(/=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(StatusAndSex -> StatusAndSex -> Bool))), ["(==)", "(/=)"]),
@@ -55,7 +55,7 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(Housing -> Housing -> Bool))), ["(==)", "(/=)"]),
             -- Any Type
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Int -> Int -> Int))), ["if'"]),
-            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> GermanClass -> GermanClass -> GermanClass))), ["if'","if'","if'","if'","if'","if'","if'","if'"]),
+            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> GermanClass -> GermanClass -> GermanClass))), ["if'"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> AccountStatus -> AccountStatus -> AccountStatus))), ["if'"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> CreditHistory -> CreditHistory -> CreditHistory))), ["if'"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Purpose -> Purpose -> Purpose))), ["if'"]),
@@ -86,13 +86,13 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(Job))), [(fmap show (enumUniform UnemployedOrUnskilledNonResident HighlySkilled ))])
           ],
       targetType = (Ref.SomeTypeRep (Ref.TypeRep @(AccountStatus -> Int -> CreditHistory -> Purpose -> Int -> Savings -> EmploymentStatus -> Int -> StatusAndSex -> OtherDebtors -> Int -> Property -> Int -> OtherPlans -> Housing -> Int -> Job -> Int -> Bool -> Bool -> GermanClass))),
-      maxDepth = 8,
+      maxDepth = 9,
       weights =
         ExpressionWeights
-          { lambdaSpucker = 1,
-            lambdaSchlucker = 2,
-            symbol = 30,
-            variable = 10,
+          { lambdaSpucker = 0,
+            lambdaSchlucker = 10,
+            symbol = 100,
+            variable = 5,
             constant = 5
           }
     }
@@ -151,6 +151,7 @@ data LamdaExecutionEnv = LamdaExecutionEnv
 data FittnesRes = FittnesRes
   { total :: R,
     fitnessTotal :: R,
+    costAccordingToDataset :: N,
     fitnessGeoMean :: R,
     fitnessMean :: R,
     accuracy :: R,
@@ -189,8 +190,9 @@ evalResults ex trs = do
 evalResult :: LamdaExecutionEnv -> TypeRequester -> (AccountStatus -> Int -> CreditHistory -> Purpose -> Int -> Savings -> EmploymentStatus -> Int -> StatusAndSex -> OtherDebtors -> Int -> Property -> Int -> OtherPlans -> Housing -> Int -> Job -> Int -> Bool -> Bool -> GermanClass) -> (TypeRequester, FittnesRes)
 evalResult ex tr result = ( tr,
       FittnesRes
-        { total = score,
+        { total = (biasSmall - 1) - (fromIntegral costAccordingToDS),
           fitnessTotal = fitness',
+          costAccordingToDataset = costAccordingToDS,
           fitnessMean = meanOfAccuricyPerClass resAndTarget,
           fitnessGeoMean = geomeanOfDistributionAccuracy resAndTarget,
           accuracy = acc,
@@ -201,7 +203,8 @@ evalResult ex tr result = ( tr,
     where
     res = map (\(a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t) -> result a b c d e f g h i j k l m n o p q r s t) (fst (dset ex))
     resAndTarget = (zip (snd (dset ex)) res)
-    acc = (foldr (\ts s -> if ((fst ts) == (snd ts)) then s + 1 else s) 0 resAndTarget) / fromIntegral (length resAndTarget)
+    acc = (foldr (\(actual,predicted) s -> if (actual == predicted) then s + 1 else s) 0 resAndTarget) / fromIntegral (length resAndTarget)
+    costAccordingToDS = (foldr (\(actual,predicted) s -> if ((actual) == (predicted)) then s else (if actual == Deny then s+5 else s+1)) 0 resAndTarget)
     biasSmall = exp ((-(fromIntegral (countTrsR tr))) / 1000) -- 0 (schlecht) bis 1 (gut)
     fitness' = meanOfAccuricyPerClass resAndTarget
     score = fitness' + (biasSmall - 1)

lambda/src/LambdaDatasets/IrisDataset.hs

@@ -34,12 +34,17 @@ lE =
   LambdaEnviroment
     { functions =
         Map.fromList
-          [ ((Ref.SomeTypeRep (Ref.TypeRep @(Float -> Float -> Float))), ["(+)", "(-)", "(*)"]),
-            ((Ref.SomeTypeRep (Ref.TypeRep @(Float -> Float -> Bool))), ["(>)", "(==)", "(>=)"]),
-            ((Ref.SomeTypeRep (Ref.TypeRep @(IrisClass -> IrisClass -> Bool))), ["(==)"]),
-            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Float -> Float -> Float))), ["if'","if'","if'","if'","if'","if'","if'","if'"]),
+          [  -- Math
+            ((Ref.SomeTypeRep (Ref.TypeRep @(Float -> Float -> Float))), ["(+)", "(-)", "(*)"]),
+            -- Logic
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Bool -> Bool))), ["(&&)", "(||)"]),
-            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> IrisClass -> IrisClass -> IrisClass))), ["if'","if'","if'","if'","if'","if'","if'","if'","if'","if'"])
+            -- Ordered
+            ((Ref.SomeTypeRep (Ref.TypeRep @(Float -> Float -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
+            -- Eq
+            ((Ref.SomeTypeRep (Ref.TypeRep @(IrisClass -> IrisClass -> Bool))), ["(==)","(/=)"]),
+            -- Any Type
+            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Float -> Float -> Float))), ["if'"]),
+            ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> IrisClass -> IrisClass -> IrisClass))), ["if'"])
           ],
       constants =
         Map.fromList
@@ -48,13 +53,13 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(IrisClass))), [(fmap show (enumUniform Setosa Versicolor :: RVar IrisClass))])
           ],
       targetType = (Ref.SomeTypeRep (Ref.TypeRep @(Float -> Float -> Float -> Float -> IrisClass))),
-      maxDepth = 10,
+      maxDepth = 9,
       weights =
         ExpressionWeights
-          { lambdaSpucker = 1,
-            lambdaSchlucker = 1,
-            symbol = 30,
-            variable = 100,
+          { lambdaSpucker = 0,
+            lambdaSchlucker = 10,
+            symbol = 100,
+            variable = 5,
             constant = 5
           }
     }
@@ -63,7 +68,7 @@ lEE :: LamdaExecutionEnv
 lEE =
   LamdaExecutionEnv
     { -- For now these need to define all available functions and types. Generic functions can be used.
-      imports = ["LambdaDatasets.IrisDataset"],
+      imports = ["LambdaDatasets.IrisDefinition"],
       training = True,
       trainingData =
         ( map fst (takeFraktion 0.8 irisTrainingData),
@@ -84,7 +89,7 @@ shuffledLEE = do
   itD <- smpl $ shuffle irisTrainingData
   return  LamdaExecutionEnv
     { -- For now these need to define all available functions and types. Generic functions can be used.
-      imports = ["LambdaDatasets.IrisDataset"],
+      imports = ["LambdaDatasets.IrisDefinition"],
       training = True,
       trainingData =
         ( map fst (takeFraktion 0.8 itD),
@@ -150,7 +155,7 @@ evalResults ex trs = do
 evalResult :: LamdaExecutionEnv -> TypeRequester -> (Float -> Float -> Float -> Float -> IrisClass) -> (TypeRequester, FittnesRes)
 evalResult ex tr result = ( tr,
       FittnesRes
-        { total = score,
+        { total = acc * 100 + (biasSmall - 1),
           fitnessTotal = fitness',
           fitnessMean = meanOfAccuricyPerClass resAndTarget,
           fitnessGeoMean = geomeanOfDistributionAccuracy resAndTarget,

lambda/src/LambdaDatasets/NurseryDataset.hs

@@ -37,7 +37,7 @@ lE =
           [ -- Math
             -- Logic
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Bool -> Bool))), ["(&&)", "(||)"]),
-            -- Ordered Enums
+            -- Ordered
             ((Ref.SomeTypeRep (Ref.TypeRep @(NurseryClass -> NurseryClass -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Parents -> Parents -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(HasNurs -> HasNurs -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
@@ -47,7 +47,7 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(Finance -> Finance -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Social -> Social -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Health -> Health -> Bool))), ["(>)", "(==)", "(/=)", "(>=)"]),
-            -- Eq Enum
+            -- Eq
             -- Any Type
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> Int -> Int -> Int))), ["if'"]),
             ((Ref.SomeTypeRep (Ref.TypeRep @(Bool -> NurseryClass -> NurseryClass -> NurseryClass))), ["if'","if'","if'","if'","if'","if'","if'","if'"]),
@@ -74,13 +74,13 @@ lE =
             ((Ref.SomeTypeRep (Ref.TypeRep @(Health))), [(fmap show (enumUniform NotRecommendHealth PriorityHealth ))])
           ],
       targetType = (Ref.SomeTypeRep (Ref.TypeRep @(Parents -> HasNurs -> Form -> Children -> Housing -> Finance -> Social -> Health -> NurseryClass))),
-      maxDepth = 8,
+      maxDepth = 9,
       weights =
         ExpressionWeights
-          { lambdaSpucker = 1,
-            lambdaSchlucker = 2,
-            symbol = 30,
-            variable = 20,
+          { lambdaSpucker = 0,
+            lambdaSchlucker = 10,
+            symbol = 100,
+            variable = 5,
             constant = 5
           }
     }

lambda/src/Main.hs

@@ -9,8 +9,8 @@ import Pretty
 import Protolude hiding (for)
 import System.IO
 -- import LambdaDatasets.IrisDataset
-import LambdaDatasets.NurseryDataset
--- import LambdaDatasets.GermanDataset
+-- import LambdaDatasets.NurseryDataset
+import LambdaDatasets.GermanDataset
 import Debug.Trace as DB
 import qualified Data.Map.Strict as Map
 
@@ -35,7 +35,7 @@ options =
       ( long "population-size"
           <> short 'p'
           <> metavar "N"
-          <> value 400
+          <> value 100
           <> help "Population size"
       )
 
@@ -59,7 +59,7 @@ main =
       selectionType = Tournament 3,
       termination = (steps (iterations opts)),
       poulationSize = (populationSize opts),
-      stepSize = 120,
+      stepSize = 90,
       elitismRatio = 5/100
     }
     pop' <- runEffect (for (run cfg) logCsv)