Sklearn推出你自己的估计器，检查估计器错误

from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils.validation import check_X_y, check_array, check_is_fitted

class MyEstimator(BaseEstimator, ClassifierMixin):
    def __init__(self, parameter1=1, parameter2='default'):
        self.parameter1 = parameter1
        self.parameter2 = parameter2
        # 其他初始化操作

    def fit(self, X, y):
        # 检查输入数据的合法性
        X, y = check_X_y(X, y)
        # 训练模型的逻辑
        # 可以使用self.parameter1和self.parameter2来访问参数
        # 训练完成后，设置self.is_fitted_为True
        self.is_fitted_ = True
        return self

    def predict(self, X):
        # 检查输入数据的合法性
        check_is_fitted(self, 'is_fitted_')
        X = check_array(X)
        # 预测的逻辑
        # 返回预测结果

    def get_params(self, deep=True):
        return {'parameter1': self.parameter1, 'parameter2': self.parameter2}

    def set_params(self, **parameters):
        for parameter, value in parameters.items():
            setattr(self, parameter, value)
        return self

estimator = MyEstimator(parameter1=2, parameter2='custom')
estimator.fit(X_train, y_train)
predictions = estimator.predict(X_test)