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名前 'DataFrameSelector'が定義されていません

私は現在"Scikit-Learn＆TensorFlowによる実践的な機械学習"を読んでいます。変換パイプラインコードを再作成しようとすると、エラーが発生します。どうすれば修正できますか？

コード：

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler

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

housing_num_tr = num_pipeline.fit_transform(housing_num)

from sklearn.pipeline import FeatureUnion

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

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()),
                        ])

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

# And we can now run the whole pipeline simply:

housing_prepared = full_pipeline.fit_transform(housing)
housing_prepared

エラー：

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-350-3a4a39e5bc1c> in <module>()
     43 
     44 num_pipeline = Pipeline([
---> 45                          ('selector', DataFrameSelector(num_attribs)),
     46                          ('imputer', Imputer(strategy = "median")),
     47                          ('attribs_adder', CombinedAttributesAdder()),

NameError: name 'DataFrameSelector' is not defined
pythonscikit-learnpipeline
8
Isaac A

DataFrameSelectorが見つからないため、インポートする必要があります。これはsklearnの一部ではありませんが、同じ名前のものが sklearn-features で利用可能です：

from sklearn_features.transformers import DataFrameSelector

（ [〜＃〜] docs [〜＃〜] ）

18
Stephen Rauch
from sklearn.base import BaseEstimator, TransformerMixin

class DataFrameSelector(BaseEstimator, TransformerMixin):
    def __init__(self, attribute_names):
        self.attribute_names=attribute_names
    def fit(self, X, y=None):
        return self
    def transform(self, X):
        return X[self.attribute_names].values

これは動作するはずです。

9
dr2509

SklearnとTensorflowを使ってHands of Machine Learningをフォローしている場合、それは次のページ、カスタムメイドのデータフレームジェネレーターにあります

from sklearn.pipeline import FeatureUnion
class DataFrameSelector(BaseEstimator, TransformerMixin):
    def __init__(self, attribute_names):
        self.attribute_names = attribute_names
    def fit(self, X, y=None):
        return self
    def transform(self, X):
        return X[self.attribute_names].values
4
Shafay
from sklearn.pipeline import FeatureUnion
class DataFrameSelector(BaseEstimator, TransformerMixin):
    def __init__(self, attribute_names):
        self.attribute_names = attribute_names
    def fit(self, X, y=None):
        return self
    def transform(self, X):
        return X[self.attribute_names].values

うまくいくかもしれません。

1
Navid