如何在执行sklearn Column Transformer后获取新列的名称

from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import OneHotEncoder
from sklearn.pipeline import Pipeline

# 假设有两个特征列，一个是数值型特征，一个是分类特征
numeric_features = ['age']
categorical_features = ['gender']

# 定义数值型特征的转换器
numeric_transformer = Pipeline(steps=[
    ('numeric_encoder', OneHotEncoder())
])

# 定义分类特征的转换器
categorical_transformer = Pipeline(steps=[
    ('categorical_encoder', OneHotEncoder())
])

# 定义Column Transformer，将两个转换器应用于对应的特征列
preprocessor = ColumnTransformer(
    transformers=[
        ('numeric', numeric_transformer, numeric_features),
        ('categorical', categorical_transformer, categorical_features)
    ])

# 假设有一个包含特征列的数据集X
X = ...

# 执行Column Transformer进行转换
X_transformed = preprocessor.fit_transform(X)

# 获取新列的名称
new_column_names = []
for transformer_name, transformer, features in preprocessor.transformers_:
    if transformer_name != 'remainder':
        if hasattr(transformer, 'get_feature_names_out'):
            # 如果转换器有get_feature_names_out方法，则使用该方法获取新列的名称
            new_column_names.extend(transformer.get_feature_names_out(features))
        else:
            # 否则，使用原始特征列的名称
            new_column_names.extend(features)

# 打印新列的名称
print(new_column_names)