prediction.py

import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
import joblib
scal=StandardScaler()
clfr = joblib.load("heartmodel.pkl")
 
def preprocess(age,sex,cp,trestbps,restecg,chol,fbs,thalach,exang,oldpeak,slope,ca,thal ):   
 
    if sex=="male":
        sex=1 
    else: sex=0 
    if cp=="Typical angina":
        cp=0
    elif cp=="Atypical angina":
        cp=1
    elif cp=="Non-anginal pain":
        cp=2
    elif cp=="Asymptomatic":
        cp=3
    if exang=="Yes":
        exang=1
    elif exang=="No":
        exang=0
    if fbs=="Yes":
        fbs=1
    elif fbs=="No":
        fbs=0
    if slope=="Upsloping: better heart rate with excercise(uncommon)":
        slope=0
    elif slope=="Flatsloping: minimal change(typical healthy heart)":
          slope=1
    elif slope=="Downsloping: signs of unhealthy heart":
        slope=2  
    if thal=="fixed defect: used to be defect but ok now":
        thal=6
    elif thal=="reversable defect: no proper blood movement when excercising":
        thal=7
    elif thal=="normal":
        thal=2.31
    if restecg=="Nothing to note":
        restecg=0
    elif restecg=="ST-T Wave abnormality":
        restecg=1
    elif restecg=="Possible or definite left ventricular hypertrophy":
        restecg=2
    user_input=[age,sex,cp,trestbps,restecg,chol,fbs,thalach,exang,oldpeak,slope,ca,thal]
    df=pd.read_csv('heart.csv')
    y = df["target"]
    X = df.drop('target',axis=1)
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state = 0)
    scaler = StandardScaler()
    X_train = scaler.fit_transform(X_train)
    user_input=np.array(user_input)
    user_input=user_input.reshape(1,-1)
    user_input=scaler.transform(user_input)
    print(user_input)
    prediction = clfr.predict(user_input)
    print(int(prediction))

    return int(prediction)

# if __name__ == '__main__':
#     t=preprocess(39,"male","Non-anginal pain",130,"ST-T Wave abnormality",250,"Yes",187,"Yes",2,"Downsloping: signs of unhealthy heart",2,"normal")
#     print(int(t))