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src/a/z/AZOrange-HEAD/azorange/AZutilities/getUnbiasedAccuracy.py   AZOrange(Download)
                    else:
                        res = evalUtilities.crossValidation([MLmethods[ml]], trainData, folds=5, stratified=orange.MakeRandomIndices.StratifiedIfPossible, random_generator = random.randint(0, 100))
                        R2 = evalUtilities.R2(res)[0]
                        optAcc[ml].append(R2)
                else:
                            else:
                                    res = evalUtilities.crossValidation([MLmethods[ml]], trainData, folds=5, stratified=orange.MakeRandomIndices.StratifiedIfPossible, random_generator = random.randint(0, 100))
                                    R2 = evalUtilities.R2(res)[0]
                                    optAcc[ml].append(R2)
                    else:
                                else:
                                    res = evalUtilities.crossValidation([MLmethods[ml]], trainData, folds=5, stratified=orange.MakeRandomIndices.StratifiedIfPossible, random_generator = random.randint(0, 100))
                                    R2 = evalUtilities.R2(res)[0]
                                    optAcc[ml].append(R2)
 

src/a/z/AZOrange-HEAD/azorange/AZutilities/competitiveWorkflow.py   AZOrange(Download)
                else:
                    res = orngTest.crossValidation([learners[ML]], trainData, folds=5, strat=orange.MakeRandomIndices.StratifiedIfPossible, randomGenerator = random.randint(0, 100))
                    R2 = evalUtilities.R2(res)[0]  
                    MLMethods[ML]["optAcc"] = R2
                miscUtilities.removeDir(runPath)