Imprecise intervals/labels by pd.cut
#### Code Sample
```python
import pandas as pd

x = [0, 1, 2, 3, 4]
res = pd.cut(x, (0, 2, 4), include_lowest=True)
print(res, '\n')

for val in res:
    print(repr(val))
```
#### Output
```
[(-0.001, 2.0], (-0.001, 2.0], (-0.001, 2.0], (2.0, 4.0], (2.0, 4.0]]
Categories (2, interval[float64]): [(-0.001, 2.0] < (2.0, 4.0]] 

Interval(-0.001, 2.0, closed='right')
Interval(-0.001, 2.0, closed='right')
Interval(-0.001, 2.0, closed='right')
Interval(2.0, 4.0, closed='right')
Interval(2.0, 4.0, closed='right')
```
#### Problem description

The correct cutting behaviour but the labels are awkward (given the input), they leak the internal adjustments used to do the cutting.  The expected output has precise intervals/labels. This is a regression from the previous version `0.19.2`.

#### Expected Output
```
[[0, 2], [0, 2], [0, 2], (2, 4], (2, 4]]
Categories (2, interval[int64]): [[0, 2] < (2, 4]]

Interval(0, 2, closed='both')
Interval(0, 2, closed='both')
Interval(0, 2, closed='both')
Interval(2, 4, closed='right')
Interval(2, 4, closed='right')
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------

commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.6-gentoo-r1
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.utf8
LANG: en_US.utf8
LOCALE: en_US.UTF-8

pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 35.0.2
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 6.0.0
sphinx: 1.5.5
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.1
feather: None
matplotlib: 2.0.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
