如何在CalibratedClassifierCV后添加自定义RuleBasedClassifier到sklearn pipeline？

from sklearn.pipeline import Pipeline
from sklearn.calibration import CalibratedClassifierCV
from sklearn.base import BaseEstimator, ClassifierMixin

class RuleBasedClassifier(BaseEstimator, ClassifierMixin):
    def __init__(self, rule_param):
        self.rule_param = rule_param
        # 其他初始化操作
    
    def fit(self, X, y):
        # 模型训练逻辑
        # 可以使用self.rule_param来调整模型行为
        return self
    
    def predict(self, X):
        # 模型预测逻辑
        return predictions

pipeline = Pipeline([
    ('calibrated', CalibratedClassifierCV()),
    ('rule_based', RuleBasedClassifier(rule_param))
])

pipeline.fit(X_train, y_train)
predictions = pipeline.predict(X_test)