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src/a/z/AZOrange-HEAD/azorange/trainingMethods/AZorngConsensus.py   AZOrange(Download)
                    ex[attr] = "NA"
 
            trainDomain.append(ex)
            trainDomain.save(os.path.join(dirPath,"trainDomain.tab"))
 

src/a/z/AZOrange-HEAD/orange/OrangeWidgets/Data/OWRank.py   AZOrange(Download)
        for attr in self.attributeOrder:
            cont = attr.varType == orange.VarTypes.Continuous
            attrData.append([attr.name, cont, cont and "?" or len(attr.values)] + [meas[attr] or "?" for meas in measDicts])
 
        self.send("ExampleTable Attributes", attrData)

src/a/z/AZOrange-HEAD/azorange/AZutilities/similarityMetrics.py   AZOrange(Download)
 
        tab = dataUtilities.DataTable(domain)
        tab.append(dat)
 
        MD = calcMahalanobis(trainData, tab, invCovMatFile, centerFile, dataTableFile, domain)

src/a/z/AZOrange-HEAD/azorange/AZutilities/getBBRCDesc.py   AZOrange(Download)
                else:
                    newEx[d] = 0.0
            newData.append(newEx)
        if self.verbose: 
            if nCompounds < 100:

src/a/z/AZOrange-HEAD/tests/source/AZdataUtilitiesTest.py   AZOrange(Download)
        data = dataUtilities.DataTable(orange.Domain(self.multiClassData.domain.variables.native()))
        for ex in self.multiClassData:
            data.append(ex)
        multiclassScaler = dataUtilities.scalizer(scaleClass = True, data=data)
        scaledData = multiclassScaler.scaleAndContinuizeData(data)