Python crossValidationSVM1Stage примеры использования

Пример #1

Файл: main.py Проект: khoaipx/SRL

listIDTotal, listTreeTotal, listRelTotal, listArgTotal = lib.filterData(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)
lib.makePredicatenode(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)

print 'Getting Feature'
# listLabel, listFeature, listCount = lib.getFeature(listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking, listWordName, listCluster)

listLabel, listFeature, listCount = lib.getFeatureAllNode(listIDTotal, listTreeTotal, listRelTotal, listArgTotal, listWordName, listCluster)
lib.checkUnderscore(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)

listLabel = lib.getListLabelReduce(listLabel, listLabelOriginal)

listLE, leLabel, listEncode = lib.getLabelEncoderParameter(listFeature, listLabel)
print 'Separating Data'
# groupInfo, groupListLabel, groupListFeature = lib.kFold(listID1Rel, listTree1Rel, listRel1Rel, listArg1Rel, listWordName, listCluster, foldNumber, listLabelOriginal)
groupInfo, groupListLabel, groupListFeature, listOfListNumArgPerSen = lib.kFold(listIDTotal, listTreeTotal, listRelTotal, listArgTotal, listWordName, listCluster, foldNumber, listLabelOriginal)

print 'Transforming Data'
listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listOfListNumArg, listOfListPredicateType = lib.crossValidation(groupListLabel, groupListFeature, listLE, leLabel, foldNumber, groupInfo)
print 'Running Algorithm'

listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionClassify1Stage, listRecallClassify1Stage, listF1ScoreClassify1Stage, listPrecision1Stage, listRecall1Stage, listF1Score1Stage, listOfListLabelPredict, listOfListLabelILP, listDensityMatrix, listOfListVariable, listPrecisionArg, listRecallArg, listF1ScoreArg = lib.crossValidationSVM1Stage(listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listFeatureName, foldNumber, listOfListNumArg, listEncode, listOfListNumArgPerSen, listOfListPredicateType)
# listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionIden, listRecallIden, listF1ScoreIden, listPrecisionClass, listRecallClass, listF1ScoreClass, listPrecision2Stage, listRecall2Stage, listF1Score2Stage = lib.crossValidationSVM2Stage(listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listFeatureIdenName, listFeatureClassName, foldNumber, listOfListNumArg, listEncode)
print 'Output'

F1Score = lib.output1Stage(listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionClassify1Stage, listRecallClassify1Stage, listF1ScoreClassify1Stage, listPrecision1Stage, listRecall1Stage, listF1Score1Stage, listPrecisionArg, listRecallArg, listF1ScoreArg)
# F1Score = lib.output2Stage(listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionIden, listRecallIden, listF1ScoreIden, listPrecisionClass, listRecallClass, listF1ScoreClass, listPrecision2Stage, listRecall2Stage, listF1Score2Stage)

endTime = datetime.now()
print "Running time: "
print (endTime - startTime)

Пример #2

Файл: main.py Проект: khoaipx/SRL

listIDTotal, listTreeTotal, listRelTotal, listArgTotal = lib.mergeData(listID1Rel, listTree1Rel, listRel1Rel, listArg1Rel, listIDExtractFromMutliRel, listTreeExtractFromMutliRel, listRelExtractFromMutliRel, listArgExtractFromMutliRel)
# listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking = lib.chunking(listID1Rel, listTree1Rel, listRel1Rel, listArg1Rel)
#listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking = lib.chunking(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)
listIDTotal, listTreeTotal, listRelTotal, listArgTotal = lib.filterData(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)
listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking = lib.chunking(listIDTotal, listTreeTotal, listRelTotal, listArgTotal)
# lib.omitUnderscore(listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking)

print 'Getting Feature'
listLabel, listFeature = lib.getFeature(listIDAfterChunking, listTreeAfterChunking, listRelAfterChunking, listArgAfterChunking, listWordName, listCluster)

listLabel = lib.getListLabelReduce(listLabel, listLabelOriginal)

listLE, leLabel, listEncode = lib.getLabelEncoderParameter(listFeature, listLabel)
print 'Separating Data'
# groupInfo, groupListLabel, groupListFeature = lib.kFold(listID1Rel, listTree1Rel, listRel1Rel, listArg1Rel, listWordName, listCluster, foldNumber, listLabelOriginal)
groupInfo, groupListLabel, groupListFeature = lib.kFold(listIDTotal, listTreeTotal, listRelTotal, listArgTotal, listWordName, listCluster, foldNumber, listLabelOriginal)

print 'Transforming Data'
listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listOfListNumArg = lib.crossValidation(groupListLabel, groupListFeature, listLE, leLabel, foldNumber, groupInfo)
print 'Running Algorithm'

listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionClassify1Stage, listRecallClassify1Stage, listF1ScoreClassify1Stage, listPrecision1Stage, listRecall1Stage, listF1Score1Stage = lib.crossValidationSVM1Stage(listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listFeatureName, foldNumber, listOfListNumArg, listEncode)
#listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionIden, listRecallIden, listF1ScoreIden, listPrecisionClass, listRecallClass, listF1ScoreClass, listPrecision2Stage, listRecall2Stage, listF1Score2Stage = lib.crossValidationMaxEnt2Stage(listOfListFeatureTrain, listOfListFeatureTest, listOfListLabelTrain, listOfListLabelTest, listFeatureIdenName, listFeatureClassName, foldNumber, listOfListNumArg, listEncode)
print 'Output'

F1Score = lib.output1Stage(listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionClassify1Stage, listRecallClassify1Stage, listF1ScoreClassify1Stage, listPrecision1Stage, listRecall1Stage, listF1Score1Stage)
#F1Score = lib.output2Stage(listPrecisionChunking, listRecallChunking, listF1ScoreChunking, listPrecisionIden, listRecallIden, listF1ScoreIden, listPrecisionClass, listRecallClass, listF1ScoreClass, listPrecision2Stage, listRecall2Stage, listF1Score2Stage)

endTime = datetime.now()
print "Running time: "
print (endTime - startTime)