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* To make the python module, type ```./build.sh``` in the root directory of project
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* Install with `python setup.py install` from this directory.
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* Refer also to the walk through example in [demo folder](../demo/guide-python)
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* **NOTE**: if you want to run XGBoost 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_examples.py demo.
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* **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.
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R
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