Update app.py

app.py

@@ -1,9 +1,3 @@
-from sklearn.model_selection import train_test_split
-from sklearn.linear_model import LinearRegression,Lasso,Ridge
-from sklearn.preprocessing import OneHotEncoder, StandardScaler
-from sklearn.compose import make_column_transformer
-from sklearn.pipeline import make_pipeline
-from sklearn.metrics import r2_score
 import streamlit as st
 import pickle
 import pandas as pd
@@ -26,5 +20,6 @@ def predict():
     # print(type(location),type(bhk),type(bath),type(sqft))
     return np.abs(np.round(prediction,2))
 
-if(st.button('click')):
+if(st.button('Check_the_price')):
+    st.title("The approximate price of this property is: ")
     st.title(predict())