Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

polish README.md with more information for PR #450

Browse Source
This commit is contained in:
phunterlau 2015-08-20 12:33:28 -07:00
parent db444c4a08
commit 5e81a210ce
1 changed files with 20 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
python-package/README.md
View File

@ -1,7 +1,26 @@
XGBoost Python Package
======================
Installation
------------
We are on [PyPI](https://pypi.python.org/pypi/xgboost) now. For stable version, please install using pip:
* ```pip install xgboost```
* Note for windows users: this pip installation may not work on some windows environment. Please install from github if pip doesn't work on windows.
For up-to-date version, please install from github.
* To make the python module, type ```./build.sh``` in the root directory of project
* Make sure you have [setuptools](https://pypi.python.org/pypi/setuptools)
* Install with `python setup.py install` from this directory.
Examples
------
* Refer also to the walk through example in [demo folder](../demo/guide-python)
* **NOTE**: if you want to run XGBoost process in parallel using the fork backend for joblib/multiprocessing, you must build XGBoost without support for OpenMP by `make no_omp=1`. Otherwise, use the forkserver (in Python 3.4) or spawn backend. See the sklearn_parallel.py demo.
* See also the [example scripts](../demo/kaggle-higgs) for Kaggle Higgs Challenge, including [speedtest script](../demo/kaggle-higgs/speedtest.py) on this dataset.
Note
-----
* If you want to build xgboost on Mac OS X with multiprocessing support where clang in XCode by default doesn't support, please install gcc 4.9 or higher using [homebrew](http://brew.sh/) ```brew tap homebrew/versions; brew install gcc49```
* If you want to run XGBoost process in parallel using the fork backend for joblib/multiprocessing, you must build XGBoost without support for OpenMP by `make no_omp=1`. Otherwise, use the forkserver (in Python 3.4) or spawn backend. See the [sklearn_parallel.py](../demo/guide-python/sklearn_parallel.py) demo.