def predict():
input_features = [x for x in request.form.values()]
#print(input_features)
bath = input_features[0]
balcony = input_features[1]
bhk = input_features[2]
total_sqft_int = input_features[3]
price_per_sqft = input_features[4]
area_type = input_features[5]
availability = input_features[6]
location = input_features[7]
prediction = model.predict_house_price(bath=bath,
balcony=balcony,
bhk=bhk,
total_sqft_int=total_sqft_int,
price_per_sqft=price_per_sqft,
area_type=area_type,
availability=availability,
location=location)
return render_template(
'index.html',
pridicted_value="Predicted House Price is {} lakh".format(prediction))
def predict():
#take data from form and store in each feature
input_features = [x for x in request.form.values()]
BHK = input_features[0]
Bathroom = input_features[1]
rate_persqft = input_features[2]
area_insqft = input_features[3]
construction_status = input_features[4]
Sale_type = input_features[5]
location = input_features[6]
# predict the price of house by calling model.py
predicted_price = model.predict_house_price(BHK,Bathroom,rate_persqft,area_insqft,construction_status,Sale_type,location)
# render the html page and show the output
return render_template('index.html', prediction_text='Predicted Price of House is {} (Lakhs)'.format(predicted_price))
def predict():
#take data from form and store in each feature
input_features = [x for x in request.form.values()]
bath = input_features[0]
balcony = input_features[1]
total_sqft_int = input_features[2]
bhk = input_features[3]
price_per_sqft = input_features[4]
area_type = input_features[5]
availability = input_features[6]
location = input_features[7]
# predict the price of house by calling model.py
predicted_price = model.predict_house_price(bath,balcony,total_sqft_int,bhk,price_per_sqft,area_type,availability,location)
print(predicted_price)
# render the html page and show the output
return render_template('index.html', prediction_text='Predicted Price of Bangalore House is {}'.format(predicted_price))