用OOB预测计算AUC并与测试集对比

def solve():
    from pyodide.http import open_url
    from io import StringIO
    loans_featured_csv = open_url(____).read()
    import pandas as pd
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import roc_auc_score
    from io import StringIO
    df = pd.read_csv(StringIO(____))
    num_cols=[c for c in df.select_dtypes(____).columns if c not in ['____','____'] and not c.endswith(____)]
    X=df[num_cols].fillna(____); y=df['____']
    X_tr,X_te,y_tr,y_te=train_test_split(____)
    rf=RandomForestClassifier(____)
    rf.fit(____)
    oob_auc=roc_auc_score(____)
    te_auc=roc_auc_score(y_te,rf.predict_proba(____)[:,____])
    print(____)
    print(____)
    print(____)