Difference between scikit-learn and sklearn
Question: On OS X 10.11.6 and python 2.7.10 I need to import from sklearn manifold. I
have numpy 1.8 Orc1, scipy .13 Ob1 and scikit-learn 0.17.1 installed.  
I used pip to install sklearn(0.0), but when I try to import from sklearn
manifold I get the following:

> Traceback (most recent call last): File "", line 1, in File
> "/Library/Python/2.7/site-packages/sklearn/**init**.py", line 57, in from
> .base import clone File "/Library/Python/2.7/site-packages/sklearn/base.py",
> line 11, in from .utils.fixes import signature File
> "/Library/Python/2.7/site-packages/sklearn/utils/**init**.py", line 10, in
> from .murmurhash import murmurhash3_32 File "numpy.pxd", line 155, in init
> sklearn.utils.murmurhash (sklearn/utils/murmurhash.c:5029) ValueError:
> numpy.dtype has the wrong size, try recompiling.

What is the difference between scikit-learn and sklearn? Also, I cant import
scikit-learn because of a syntax error


Answer: You might need to reinstall numpy. It doesn't seem to have installed
correctly.

`sklearn` is how you type the scikit-learn name in python.

Also, try running the standard tests in scikit-learn and check the output. You
will have detailed error information there.

Do you have `nosetests` installed? Try: `nosetests -v sklearn`. You type this
in bash, not in the python interpreter.

