import pandas as pd | |
from sklearn.model_selection import train_test_split | |
from sklearn.linear_model import LogisticRegression | |
from sklearn.metrics import accuracy_score | |
import matplotlib.pyplot as plt | |
import seaborn as sns | |
from sklearn.metrics import confusion_matrix | |
from sklearn.metrics import classification_report | |
data=pd.read_csv('HeartDisease.csv') | |
print(data) | |
non_numeric_features = data.select_dtypes(include=['object']).columns.tolist() | |
print(non_numeric_features) |