Add sklearn installation in setup.py (#1157)

* fix remote bug

* add document

* add document

* update

* update

* update

* update

* fix remote issue

* fix forEach

* update doc according to comments

* update

* update

* update

* remove 'any more'

* add sklearn in setup.py

* remove sklearn in doc for MetisTuner

deployment/pypi/setup.py

@@ -75,7 +75,8 @@ setuptools.setup(
         'numpy',
         'scipy',
         'coverage',
-        'colorama'
+        'colorama',
+        'sklearn'
     ],
     classifiers = [
         'Programming Language :: Python :: 3',

docs/en_US/BuiltinTuner.md

@@ -302,10 +302,6 @@ tuner:
 
 Note that the only acceptable types of search space are `choice`, `quniform`, `uniform` and `randint`.
 
-**Installation**
-
-Metis Tuner requires [sklearn](https://scikit-learn.org/), so users should install it first. User could use `pip3 install sklearn` to install it.
-
 **Suggested scenario**
 
 Similar to TPE and SMAC, Metis is a black-box tuner. If your system takes a long time to finish each trial, Metis is more favorable than other approaches such as random search. Furthermore, Metis provides guidance on the subsequent trial. Here is an [example](https://github.com/Microsoft/nni/tree/master/examples/trials/auto-gbdt/search_space_metis.json) about the use of Metis. User only need to send the final result like `accuracy` to tuner, by calling the nni SDK. [Detailed Description](./MetisTuner.md)

setup.py

@@ -56,7 +56,8 @@ setup(
         'scipy',
         'schema',
         'PythonWebHDFS',
-        'colorama'
+        'colorama',
+        'sklearn'
     ],
 
     entry_points = {