Chapter 2 Analyze the Best Models and Their Errors

To analyze the relative importance of each attribute for making accurate predictions, the book use the next code (with its output):

```pycon
>>> feature_importances = grid_search.best_estimator_.feature_importances_
>>> feature_importances
array([7.33442355e-02, 6.29090705e-02, 4.11437985e-02, 1.46726854e-02,
1.41064835e-02, 1.48742809e-02, 1.42575993e-02, 3.66158981e-01,
5.64191792e-02, 1.08792957e-01, 5.33510773e-02, 1.03114883e-02,
1.64780994e-01, 6.02803867e-05, 1.96041560e-03, 2.85647464e-03])
```

And to add their corresponding attribute names:

```pycon
>>> extra_attribs = ["rooms_per_hhold", "pop_per_hhold", "bedrooms_per_room"]
>>> cat_encoder = full_pipeline.named_transformers_["cat"]
>>> cat_one_hot_attribs = list(cat_encoder.categories_[0])_

>>> attributes = num_attribs + extra_attribs + cat_one_hot_attribs
>>> sorted(zip(feature_importances, attributes), reverse=True)
[(0.3661589806181342, 'median_income'),
(0.1647809935615905, 'INLAND'),
(0.10879295677551573, 'pop_per_hhold'),
(0.07334423551601242, 'longitude'),
(0.0629090704826203, 'latitude'),
(0.05641917918195401, 'rooms_per_hhold'),
(0.05335107734767581, 'bedrooms_per_room'),
(0.041143798478729635, 'housing_median_age'),
(0.014874280890402767, 'population'),
(0.014672685420543237, 'total_rooms'),
(0.014257599323407807, 'households'),
(0.014106483453584102, 'total_bedrooms'),
(0.010311488326303787, '<1H OCEAN'),
(0.002856474637320158, 'NEAR OCEAN'),
(0.00196041559947807, 'NEAR BAY'),
(6.028038672736599e-05, 'ISLAND')]
```

My question is: Why do I have to add `extra_attribs`? or How do I know that I must add this attributes?

I add the output without add `extra_attribs`

```pycon
>>> feature_importances=grid_search.best_estimator_.feature_importances_

>>> #extra_attribs = ["rooms_per_hhold", "pop_per_hhold", "bedrooms_per_room"]
>>> cat_encoder = full_pipeline.named_transformers_["cat"]
>>> cat_one_hot_attribs = list(cat_encoder.categories_[0])

>>> attributes = num_attribs + cat_one_hot_attribs #+ extra_attribs
>>> sorted(zip(feature_importances, attributes), reverse=True)

[(0.303268232301214, 'median_income'),
(0.1730639450304893, 'NEAR OCEAN'),
(0.10895862174634888, 'INLAND'),
(0.0844196144263057, 'ISLAND'),
(0.07557206707255014, 'longitude'),
(0.06398786252477989, 'latitude'),
(0.06315655490931624, '<1H OCEAN'),
(0.04240720593117474, 'housing_median_age'),
(0.01829282732311651, 'total_rooms'),
(0.017560189966804522, 'population'),
(0.01689244166020893, 'total_bedrooms'),
(0.01668817806453196, 'households'),
(0.008535150622100876, 'NEAR BAY')]
```

How do I know that is wrong? Because without `extra_attribs` I can not say _apparently only one `ocean_proximity` category is really useful, so you could try dropping the others_

Thanks for your time.