执行包含自定义转换器的代码时出现问题？

Question

通过Aurelian Gideon的《O'Reilly出版的书》在定制变压器部分处理加利福尼亚住房数据集时，我运行了以下代码：-

from sklearn.base import BaseEstimator, TransformerMixin 
rooms_ix, bedrooms_ix, population_ix, households_ix = 3, 4, 5, 6

class CombinedAttributesAdder(BaseEstimator, TransformerMixin): 
    def __init__(self, add_bedrooms_per_room = True): # no *args or **kargs 
        self.add_bedrooms_per_room = add_bedrooms_per_room
    def fit(self, X, y=None): 
        return self # nothing else to do
    def transform(self, X, y=None): 
        rooms_per_household = X[:, rooms_ix] / X[:, households_ix] 
        population_per_household = X[:, population_ix] / X[:, households_ix] 
        if self.add_bedrooms_per_room: 
            bedrooms_per_room = X[:, bedrooms_ix] / X[:, rooms_ix] 
            return np.c_[X, rooms_per_household, population_per_household, bedrooms_per_room]
    else: 
        return np.c_[X, rooms_per_household, population_per_household]
    
attr_adder = CombinedAttributesAdder(add_bedrooms_per_room=False) 
housing_extra_attribs = attr_adder.transform(housing.values)

我得到的错误如下：-

File "<ipython-input-43-43e04d49480a>", line 16
    return np.c_[X, rooms_per_household, population_per_household]
    ^
IndentationError: expected an indented block

请建议如何修复它

Answer 1

价值观是一个函数

您应该使用它的“数据”来执行转换任务

比如

housing["data"]