def about():
val = int(request.args["pr"])
Dependents = int(request.args["dependence"])
tenure = float(request.args["tenure"])
OnlineSecurity = int(request.args["OnlineSecurity"])
TechSupport = int(request.args["TechSupport"])
Contract = int(request.args["Contract"])
PaperlessBilling = int(request.args["PaperlessBilling"])
MonthlyCharges = float(request.args["MonthlyCharges"])
TotalCharges = float(request.args["TotalCharges"])
#data0=([Dependents,tenure,OnlineSecurity,TechSupport,Contract,PaperlessBilling,MonthlyCharges,TotalCharges])
data0 = ({
'Dependents': [Dependents],
'tenure': [tenure],
'OnlineSecurity': [OnlineSecurity],
'TechSupport': [TechSupport],
'Contract': [Contract],
'PaperlessBilling': [PaperlessBilling],
'MonthlyCharges': [MonthlyCharges],
'TotalCharges': [TotalCharges]
})
data = pd.DataFrame(data0)
return str(algorithm.predData(algorithm.perprocess(df), data, val))
def pred():
pr = int(request.args["pr"])
return "Accuracy " + algorithm.predict(
algorithm.perprocess(df), pr
) + "<a href=adddata>" + "<br>" + "<br>" + "<br>" + "<br>" + "<input type=button value='go to predict'/adddata/'></a>"
def prep():
return algorithm.perprocess(df).to_html()