heart.py

import pandas as pd
import numpy as np
import joblib
import warnings
warnings.filterwarnings('ignore',category=FutureWarning)
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import cross_validate

data=pd.read_csv('heart.csv')
data['trestbps']=np.log(data['trestbps'])
data=data.drop(['fbs'],axis=1)
data=data.drop(['ca'],axis=1)
data['chol']=np.log(data['chol'])
target=data['target']
print(data.shape[1])

np.random.shuffle(data.values)
data=data.drop(['target'],axis=1)
print(data.columns)
sc=StandardScaler()
data=sc.fit_transform(data)

lr=LogisticRegression()
lr.fit(data,target)
cv_result=cross_validate(lr,data,target,cv=10)
print(cv_result)
joblib.dump(lr,'heart')