german with cost matrix
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				| @ -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 = acc * 100 + (biasSmall - 1), | ||||
|         { 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) | ||||
|  | ||||
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