Python PredictionToOut示例

示例#1

def main():
    SVMNormalisation()
    fichierResultat = LaunchSVM("SVMtrain",
                                "texteDT",
                                nameTest="SVMtest",
                                nameModel="ModelFromTPDataWithoutBW")
    PredictionToOut(fichierResultat)

示例#2

文件： RNNscript_standardAndTP-DTVwithNoneAnnoteeAndTP.py 项目： nalfein84/detectiondesentimentdanslestweets

def main():
    RNN_Normalisation()
    InitDocToVecParameter(["AnnotedAndTPdata", "texteDT", "70kTweet"],
                          50,
                          10,
                          90,
                          TestingDocToVec=True)
    RNNscript("AnnotedAndTPdata",
              "texteDT",
              90,
              epochs=100,
              nameModel="standardsWithAnnotedAndTP-DTVwithNoneAnnoted")
    PredictionToOut("GenerationFichier/RNNtestResult.txt")

示例#3

文件： RNNscript_standardDTVwithNoneAnnoteeAndCommittee.py 项目： nalfein84/detectiondesentimentdanslestweets

def main():
    #RNN_Normalisation()
    InitDocToVecParameter(["JSONdata", "texteDT", "70kTweet"],
                          45,
                          10,
                          95,
                          TestingDocToVec=True)
    RNNscript("JSONdata",
              "texteDT",
              90,
              epochs=100,
              nameModel="standardsWithAnnotedTrainDataDTVwithNoneAnnoted",
              typeRNN="Committee",
              TailleDuComitee=20)
    PredictionToOut("GenerationFichier/RNNtestResult.txt")

示例#4

文件： RNNscript_standardComitee.py 项目： nalfein84/detectiondesentimentdanslestweets

def main():
    RNN_Normalisation()
    InitDocToVecParameter(["JSONdata", "texteDT"],
                          100,
                          20,
                          98,
                          TestingDocToVec=True)
    RNNscript("JSONdata",
              "texteDT",
              80,
              epochs=100,
              nameModel="standardsWithAnnotedTrainDataAndCommitee",
              typeRNN="Committee",
              TailleDuComitee=10)
    PredictionToOut("GenerationFichier/RNNtestResult.txt")

示例#5

def main():
    SVMNormalisation()
    fichierResultat = LaunchSVM("JSONdata",
                                "texteDT",
                                nameModel="SimpleModelFromHand")
    PredictionToOut(fichierResultat)

示例#6

文件： SVMscript_standardSVMWithDataFromHandAndTP.py 项目： nalfein84/detectiondesentimentdanslestweets

def main():
    SVMNormalisation()
    ConcatFile("Normalisation/JSONdata.txt", "Normalisation/SVMtrain.txt", "Normalisation/TPandJson.txt", withLabel=True)
    fichierResultat = LaunchSVM("TPandJson", "texteDT", nameModel="SimpleModelFromHandAndTP")
    PredictionToOut(fichierResultat)