逻辑回归-Heart分类

def solve():
    import pandas as pd
    from sklearn.linear_model import LogisticRegression
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import accuracy_score, roc_auc_score
    from sklearn.preprocessing import StandardScaler
    df = pd.read_csv('https://liangdaima.com/static/data/heart.csv')
    X = df.drop('target', axis=1)
    y = df['target']
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
    scaler = StandardScaler()
    X_train = scaler.fit_transform(X_train)
    X_test = scaler.transform(X_test)
    lr = LogisticRegression(random_state=42)
    lr.fit(X_train, y_train)
    y_pred = lr.predict(X_test)
    y_proba = lr.predict_proba(X_test)[:, 1]
    print('准确率:', round(accuracy_score(y_test, y_pred), 4))
    print('ROC AUC:', round(roc_auc_score(y_test, y_proba), 4))