Upload app.py

app.py

@@ -0,0 +1,24 @@
+import pandas as pd
+import pickle
+import numpy as np
+from sklearn import tree
+# Load the Random Forest CLassifier model
+filename = 'model.pkl'
+loaded_model = pickle.load(open(filename, 'rb'))
+print(loaded_model)
+
+input = [0.0,0.0,1.0,26.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,3.0,0.0,15.0,0.0,0.0,7.0,5.0,7.0]
+manualInput =[
+ [1.0,1.0,1.0,37.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,5.0,0.0,0.0,1.0,1.0,10.0,6.0,5.0]
+ #,[1.0,1.0,1.0,28.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,4.0,0.0,0.0,0.0,1.0,12.0,2.0,4.0]
+ #,[1.0,1.0,1.0,27.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,4.0,20.0,20.0,1.0,0.0,8.0,4.0,7.0]
+]
+print(input, manualInput)
+col=["HighBP","HighChol","CholCheck","BMI","Smoker","Stroke","HeartDiseaseorAttack","PhysActivity","Fruits"
+     ,"Veggies","HvyAlcoholConsump","AnyHealthcare","NoDocbcCost","GenHlth","MentHlth","PhysHlth","DiffWalk"
+     ,"Sex","Age","Education","Income"]
+ddf = pd.DataFrame(manualInput, columns=col)
+print(ddf)
+
+result = loaded_model.predict(ddf)
+print(result)