Upload app.py

app.py

@@ -32,16 +32,14 @@ ts_pred_rf = model_rf.predict(xtest)
 
 print("training accuracy is:",accuracy_score(ytrain,tr_pred_rf))
 print("testing accuracy is:",accuracy_score(ytest,ts_pred_rf))
-### PREDICTIONS
-test.join(pd.DataFrame(model_rf.predict(Y),columns=["predicted"]))[["prognosis","predicted"]]
 
 # Title of the Streamlit app
 st.title('Prognosis Prediction App')
+### PREDICTIONS
+test.join(pd.DataFrame(model_rf.predict(Y),columns=["predicted"]))[["prognosis","predicted"]]
 
-# Display a sidebar for user input
-user_input = {}
-for feature in xtrain.columns:
-    user_input[feature] = st.checkbox(feature)
+# Display a title
+st.title('Disease-Prognosis Correlation Visualization')
 
 # Calculate the correlation matrix
 corr = df_train.corr()