def classifyFunding(leadsArrays):
titlesList = [leadArray[2] for leadArray in leadsArrays]
infoTextList = ['%s %s %s' % (leadArray[3], leadArray[6], leadArray[7]) for leadArray in leadsArrays]
opportunitiesTitlesAndTexts = [[title, infoText] for title, infoText in zip(titlesList, infoTextList)]
fundingClassifier = ClassifyFundingTypeKeywordBased(opportunitiesTitlesAndTexts)
predictedFundingTypes = fundingClassifier.returnPredictedTags()
return predictedFundingTypes
def classifyFunding(leadsArrays):
titlesList = [leadArray[0] for leadArray in leadsArrays]
infoTextList = ['%s %s' % (leadArray[7], leadArray[8]) for leadArray in leadsArrays]
opportunitiesTitlesAndTexts = [[title, infoText] for title, infoText in zip(titlesList, infoTextList)]
fundingClassifier = ClassifyFundingTypeKeywordBased(opportunitiesTitlesAndTexts)
predictedFundingTypes = fundingClassifier.returnPredictedTags()
return predictedFundingTypes
def test_returnPredictedTagsFakeOpportunity(self):
fakeTitle = 'fakeTitle'
fakeText = 'this is a fake opportunity for a scholarship'
fakeOpportunity = [[fakeTitle, fakeText]]
testclassify = ClassifyFundingTypeKeywordBased(fakeOpportunity)
predictedtag = testclassify.returnPredictedTags()[0]
self.assertEqual('Scholarship', predictedtag)
def getOverallAccuracy():
pivotDataList = GetPivotTagsTitleAbstractEligibility.getListofListofItems(
)
expectedTags = GetPivotTagsTitleAbstractEligibility.getTags()
predictedTags = ClassifyFundingTypeKeywordBased(
pivotDataList).returnPredictedTags()
accuracy = ComputeAccuracy(expectedTags,
predictedTags).calculateAccuracy()
print(accuracy)
def insertPredictedTagsIntoDatabase():
pivotDataList = GetPivotTagsTitleAbstractEligibility.getListofListofItems(
)
predictedTags = ClassifyFundingTypeKeywordBased(
pivotDataList).returnPredictedTags()
db = SUDBConnect()
for i in range(len(predictedTags)):
predictedTag = predictedTags[i]
pivotTagId = str(i + 1)
db.insertUpdateOrDeleteDB("update dbo.PivotTags set Predicted='" +
predictedTag + "' where PivotTagId='" +
pivotTagId + "'")
def getPredictedTagsInsertIntoDatabase():
keywordsList = PivotLeadsGetDatabaseInfo.getKeywords()
for keyword in keywordsList:
keyword = CleanText.cleanALLtheText(keyword)
titleAbstractList = PivotLeadsGetDatabaseInfo(
keyword).getTitleAbstractList()
predictedTags = ClassifyFundingTypeKeywordBased(
titleAbstractList).returnPredictedTags()
listPivotLeadIds = PivotLeadsGetDatabaseInfo(
keyword).getPivotLeadId()
db = SUDBConnect()
for i in range(len(predictedTags)):
tag = predictedTags[i]
pivotLeadId = listPivotLeadIds[i]
db.insertUpdateOrDeleteDB("update dbo.PivotLeads set Tag='" +
tag + "' where PivotLeadId='" +
pivotLeadId + "'")
def getPredictedTagsInsertIntoDatabase():
keywordsList = GrantForwardItemsGetDatabaseInfo.getKeywords()
db = SUDBConnect()
for keyword in keywordsList:
keyword = CleanText.cleanALLtheText(keyword)
titleDescriptionList = GrantForwardItemsGetDatabaseInfo(
keyword=keyword).getTitleDescriptionList()
predictedTags = ClassifyFundingTypeKeywordBased(
titleDescriptionList).returnPredictedTags()
listGrantForwardItemIds = GrantForwardItemsGetDatabaseInfo(
keyword=keyword).getGrantForwardItemIds()
for i in range(len(predictedTags)):
tag = predictedTags[i]
grantForwardItemId = listGrantForwardItemIds[i]
db.insertUpdateOrDeleteDB(
"update dbo.GrantForwardItems set Tag='" + tag +
"' where GrantForwardItemId='" + grantForwardItemId + "'")
def getPredictedTags(self):
predictedTags = ClassifyFundingTypeKeywordBased(self.titleInfoList).returnPredictedTags()
return predictedTags
