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src/a/z/AZOrange-HEAD/azorange/AZutilities/getUnbiasedAccuracy.py   AZOrange(Download)
                    self.__log("Found SMILES attribute:"+smilesAttr)
                    if MLmethods[ml].specialType == 1:
                       trainData = dataUtilities.attributeSelectionData(trainData, [smilesAttr, trainData.domain.classVar.name]) 
                       testData = dataUtilities.attributeSelectionData(testData, [smilesAttr, testData.domain.classVar.name]) 
                       self.__log("Selected attrs: "+str([attr.name for attr in trainData.domain]))

src/a/z/AZOrange-HEAD/azorange/AZutilities/competitiveWorkflow.py   AZOrange(Download)
            log(logFile,"Found SMILES attribute:"+smilesAttr)
            if learner.specialType == 1:
               trainData = dataUtilities.attributeSelectionData(trainData, [smilesAttr, trainData.domain.classVar.name])
               log(logFile,"Selected attrs: "+str([attr.name for attr in trainData.domain]))
            else:
                if smilesAttr:
                    log(logFile,"Found SMILES attribute:"+smilesAttr)
                    trainData = dataUtilities.attributeSelectionData(trainData, [smilesAttr, trainData.domain.classVar.name])
                optInfo, SpecialModel = MLMETHODS[ML](name = ML).optimizePars(trainData, folds = 5)
                return SpecialModel