google-colaboratorysvmpredictionstreamlit

ValueError: X has 16 features, but SVC is expecting 17 features as input in disease prediction system


I am trying multiple disease prediction system and among them the error occur when trying malaria disease prediction system using svm algorithm. I have no idea how to fix the problem since other 4 disease predictions have no problem. I am new to ML field and this is the first project , so if the problem is too easy please understand me .

Error message :

alueError: X has 16 features, but SVC is expecting 17 features as input.
Traceback:
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 584, in _run_script
    exec(code, module.__dict__)
File "C:\Users\HP\Desktop\Multiple Disease Prediction System\multiple disease pred.py", line 404, in <module>
    malaria_prediction = malaria_model.predict([user_input])
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\sklearn\svm\_base.py", line 820, in predict
    y = super().predict(X)
        ^^^^^^^^^^^^^^^^^^
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\sklearn\svm\_base.py", line 433, in predict
    X = self._validate_for_predict(X)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\sklearn\svm\_base.py", line 613, in _validate_for_predict
    X = self._validate_data(
        ^^^^^^^^^^^^^^^^^^^^
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\sklearn\base.py", line 588, in _validate_data
    self._check_n_features(X, reset=reset)
File "C:\Users\HP\.conda\envs\DiseasePredictionSystem\Lib\site-packages\sklearn\base.py", line 389, in _check_n_features
    raise ValueError(

UI in the streamlit :

#Malaria Prediction Page
if selected == 'Malaria Disease Prediction':

     #page title
     st.title('Malaria Prediction using ML')
     col1, col2, col3, col4 = st.columns(4)

     with col1:
         age = st.text_input('Enter Your Age')

     with col2:
         sex = st.text_input('Male or Female [0/1] Male=0, Female=1')
         
     with col3:
        fever = st.text_input('Do you have fever? [0/1] Yes=1, No=0')

     with col4:
         cold = st.text_input('Are you feeling cold?  [0/1] Yes=1, No=0')

     with col1:
         rigor = st.text_input('Do you feel rigor:high temperature and tremble with cold ?[0/1] Yes=1, No=0')

     with col2:
         fatigue = st.text_input('Do you feel fatigue?[0/1] Yes=1, No=0')

     with col3:
         headace = st.text_input('Do you feel headache?[0/1] Yes=1, No=0')

     with col4:
         bitter_tongue = st.text_input('Bitter tougue?[0/1] Yes=1, No=0')

     with col1:
         vomitting = st.text_input('Do you Vomit? [0/1] Yes=1, No=0')

     with col2:
         diarrhea = st.text_input('Diarrhea? [0/1] Yes=1, No=0')

     with col3:
         Convulsion = st.text_input('Have you ever muscular contract? [0/1] Yes=1, No=0')

     with col4:
         Anemia = st.text_input('Do you have anemia? [0/1] Yes=1, No=0')
         
     with col1:
        jundice = st.text_input('Do you have Jaundice? [0/1] Yes=1, No=0')
        
     with col2:
            cocacola_urine = st.text_input('Colour of urine is like cocacola? [0/1] Yes=1, No=0')
            
     with col3:
            hypoglycemia = st.text_input('Low in blood sugar level? [0/1] Yes=1, No=0')
            
     with col4:
            prostraction = st.text_input('Have you collapse? [0/1] Yes=1, No=0')
            
     with col1:
        hyperpyrexia = st.text_input('Body temperature up to 106.7°F or 41.5°C?[0/1] Yes=1, No=0')

#code for prediction
     user_input = [age, sex, fever, cold, rigor, fatigue, headace, bitter_tongue, vomitting, diarrhea, Convulsion, Anemia, jundice, cocacola_urine, prostraction, hyperpyrexia]

         user_input = [float(x) for x in user_input]

         malaria_prediction = malaria_model.predict([user_input])

         if malaria_prediction[0] == 1:
             hypertension_diagnosis = 'The person has malaria disease'
         else:
             hypertension_diagnosis = 'The person does not have  malaria disease'

     st.success(malaria_diagnosis)

The google colab code of the system:

Dataset


Solution

  • Your input was missing a feature hypoglycemia, resulting in 16 inputs rather than 17. Should be:

    ...
    #code for prediction
         user_input = [age, sex, fever, cold, rigor, fatigue,
                       headace, bitter_tongue, vomitting, diarrhea,
                       Convulsion, Anemia, jundice, cocacola_urine,
                       hypoglycemia, #<---------- this was missing
                       prostraction, hyperpyrexia
                       ]
    ...
    

    You might also need to change the input to a numpy array: model.predict( np.array([user_input]) ) rather than just model.predict([user_input]). But perhaps your UI handles that automatically.