相关疑难解决方法(0)

我是机器学习的新手,我一直在使用无监督学习技术.

该图显示了我的样本数据(完全清理后)屏幕截图: 示例数据

我有两个Pipline用于清理数据:

num_attribs = list(housing_num)
cat_attribs = ["ocean_proximity"]

print(type(num_attribs))

num_pipeline = Pipeline([
    ('selector', DataFrameSelector(num_attribs)),
    ('imputer', Imputer(strategy="median")),
    ('attribs_adder', CombinedAttributesAdder()),
    ('std_scaler', StandardScaler()),
])

cat_pipeline = Pipeline([
    ('selector', DataFrameSelector(cat_attribs)),
    ('label_binarizer', LabelBinarizer())
])

然后我做了这两个管道的联合,相同的代码如下所示:

from sklearn.pipeline import FeatureUnion

full_pipeline = FeatureUnion(transformer_list=[
        ("num_pipeline", num_pipeline),
        ("cat_pipeline", cat_pipeline),
    ])

现在我试图在数据上做fit_transform 但它显示我的错误.

转型代码:

housing_prepared = full_pipeline.fit_transform(housing)
housing_prepared

错误消息:fit_transform()需要2个位置参数,但是给出了3个