Add missing file, when generating a challenge

geval.cabal

@@ -1,5 +1,5 @@
 name:                geval
-version:             1.14.0.0
+version:             1.15.0.0
 synopsis:            Machine learning evaluation tools
 description:         Please see README.md
 homepage:            http://github.com/name/project

src/GEval/Core.hs

@@ -106,7 +106,7 @@ defaultLogLossHashedSize = 10
 data Metric = RMSE | MSE | Pearson | Spearman | BLEU | GLEU | WER | Accuracy | ClippEU
               | FMeasure Double | MacroFMeasure Double | NMI
               | LogLossHashed Word32 | CharMatch | MAP | LogLoss | Likelihood
-              | BIOF1 | BIOF1Labels | TokenAccuracy | LikelihoodHashed Word32 | MAE | MultiLabelFMeasure Double
+              | BIOF1 | BIOF1Labels | TokenAccuracy | LikelihoodHashed Word32 | MAE | SMAPE | MultiLabelFMeasure Double
               | MultiLabelLogLoss | MultiLabelLikelihood
               | SoftFMeasure Double
               deriving (Eq)
@@ -145,6 +145,7 @@ instance Show Metric where
   show BIOF1Labels = "BIO-F1-Labels"
   show TokenAccuracy = "TokenAccuracy"
   show MAE = "MAE"
+  show SMAPE = "SMAPE"
   show (MultiLabelFMeasure beta) = "MultiLabel-F" ++ (show beta)
   show MultiLabelLogLoss = "MultiLabel-Logloss"
   show MultiLabelLikelihood = "MultiLabel-Likelihood"
@@ -186,6 +187,7 @@ instance Read Metric where
   readsPrec _ ('B':'I':'O':'-':'F':'1':theRest) = [(BIOF1, theRest)]
   readsPrec _ ('T':'o':'k':'e':'n':'A':'c':'c':'u':'r':'a':'c':'y':theRest) = [(TokenAccuracy, theRest)]
   readsPrec _ ('M':'A':'E':theRest) = [(MAE, theRest)]
+  readsPrec _ ('S':'M':'A':'P':'E':theRest) = [(SMAPE, theRest)]
   readsPrec _ ('M':'u':'l':'t':'i':'L':'a':'b':'e':'l':'-':'L':'o':'g':'L':'o':'s':'s':theRest) = [(MultiLabelLogLoss, theRest)]
   readsPrec _ ('M':'u':'l':'t':'i':'L':'a':'b':'e':'l':'-':'L':'i':'k':'e':'l':'i':'h':'o':'o':'d':theRest) = [(MultiLabelLikelihood, theRest)]
 
@@ -218,6 +220,7 @@ getMetricOrdering BIOF1 = TheHigherTheBetter
 getMetricOrdering BIOF1Labels = TheHigherTheBetter
 getMetricOrdering TokenAccuracy = TheHigherTheBetter
 getMetricOrdering MAE = TheLowerTheBetter
+getMetricOrdering SMAPE = TheLowerTheBetter
 getMetricOrdering (MultiLabelFMeasure _) = TheHigherTheBetter
 getMetricOrdering MultiLabelLogLoss = TheLowerTheBetter
 getMetricOrdering MultiLabelLikelihood = TheHigherTheBetter
@@ -541,6 +544,10 @@ gevalCore' MSE _ = gevalCoreWithoutInput outParser outParser itemSquaredError av
 gevalCore' MAE _ = gevalCoreWithoutInput outParser outParser itemAbsoluteError averageC id
   where outParser = getValue . TR.double
 
+gevalCore' SMAPE _ = gevalCoreWithoutInput outParser outParser smape averageC (* 100.0)
+  where outParser = getValue . TR.double
+        smape (exp, out) = (abs (exp-out)) / ((abs exp) + (abs out))
+
 gevalCore' Pearson _ = gevalCoreByCorrelationMeasure pearson
 gevalCore' Spearman _ = gevalCoreByCorrelationMeasure spearman
 

src/GEval/CreateChallenge.hs

@@ -603,6 +603,9 @@ testInContents MultiLabelLikelihood = testInContents MultiLabelLogLoss
 testInContents MultiLabelLogLoss = [hereLit|I am very sad
 I hate
 |]
+testInContents _ = [hereLit|0.72	0	0.007
+9.54	62	0.054
+|]
 
 testExpectedContents :: Metric -> String
 testExpectedContents GLEU = testExpectedContents BLEU

src/GEval/OptionsParser.hs

@@ -210,7 +210,7 @@ metricReader = many $ option auto         -- actually `some` should be used inst
                ( long "metric"            -- --metric might be in the config.txt file...
                  <> short 'm'
                  <> metavar "METRIC"
-                 <> help "Metric to be used - RMSE, MSE, Pearson, Spearman, Accuracy, LogLoss, Likelihood, F-measure (specify as F1, F2, F0.25, etc.), macro F-measure (specify as Macro-F1, Macro-F2, Macro-F0.25, etc.), multi-label F-measure (specify as MultiLabel-F1, MultiLabel-F2, MultiLabel-F0.25, etc.), MultiLabel-Likelihood, MAP, BLEU, GLEU (\"Google GLEU\" not the grammar correction metric), WER, NMI, ClippEU, LogLossHashed, LikelihoodHashed, BIO-F1, BIO-F1-Labels, TokenAccuracy, soft F-measure (specify as Soft-F1, Soft-F2, Soft-F0.25) or CharMatch" )
+                 <> help "Metric to be used - RMSE, MSE, MAE, SMAPE, Pearson, Spearman, Accuracy, LogLoss, Likelihood, F-measure (specify as F1, F2, F0.25, etc.), macro F-measure (specify as Macro-F1, Macro-F2, Macro-F0.25, etc.), multi-label F-measure (specify as MultiLabel-F1, MultiLabel-F2, MultiLabel-F0.25, etc.), MultiLabel-Likelihood, MAP, BLEU, GLEU (\"Google GLEU\" not the grammar correction metric), WER, NMI, ClippEU, LogLossHashed, LikelihoodHashed, BIO-F1, BIO-F1-Labels, TokenAccuracy, soft F-measure (specify as Soft-F1, Soft-F2, Soft-F0.25) or CharMatch" )
 
 altMetricReader :: Parser (Maybe Metric)
 altMetricReader = optional $ option auto

test/Spec.hs

@@ -84,6 +84,9 @@ main = hspec $ do
   describe "mean absolute error" $ do
     it "simple test with arguments" $
       runGEvalTest "mae-simple" `shouldReturnAlmost` 1.5
+  describe "SMAPE" $ do
+    it "simple test" $
+      runGEvalTest "smape-simple" `shouldReturnAlmost` 54.2222222222222222
   describe "Spearman's rank correlation coefficient" $ do
     it "simple test" $ do
       runGEvalTest "spearman-simple" `shouldReturnAlmost` (- 0.5735)