Merge branch 'master' into mlog
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commit
07ed143cd6
@ -116,6 +116,7 @@ Send a PR to add a one sentence description:)
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## Tools using XGBoost
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## Tools using XGBoost
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- [BayesBoost](https://github.com/mpearmain/BayesBoost) - Bayesian Optimization using xgboost and sklearn API
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- [BayesBoost](https://github.com/mpearmain/BayesBoost) - Bayesian Optimization using xgboost and sklearn API
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- [gp_xgboost_gridsearch](https://github.com/vatsan/gp_xgboost_gridsearch) - In-database parallel grid-search for XGBoost on [Greenplum](https://github.com/greenplum-db/gpdb) using PL/Python
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## Awards
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## Awards
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- [John Chambers Award](http://stat-computing.org/awards/jmc/winners.html) - 2016 Winner: XGBoost R Package, by Tong He (Simon Fraser University) and Tianqi Chen (University of Washington)
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- [John Chambers Award](http://stat-computing.org/awards/jmc/winners.html) - 2016 Winner: XGBoost R Package, by Tong He (Simon Fraser University) and Tianqi Chen (University of Washington)
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@ -23,7 +23,8 @@ print("Install libxgboost from: %s" % LIB_PATH)
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setup(name='xgboost',
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setup(name='xgboost',
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version=open(os.path.join(CURRENT_DIR, 'xgboost/VERSION')).read().strip(),
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version=open(os.path.join(CURRENT_DIR, 'xgboost/VERSION')).read().strip(),
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#version='0.4a23',
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#version='0.4a23',
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description=open(os.path.join(CURRENT_DIR, 'README.rst')).read(),
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description = "XGBoost Python Package",
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long_description=open(os.path.join(CURRENT_DIR, 'README.rst')).read(),
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install_requires=[
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install_requires=[
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'numpy',
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'numpy',
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'scipy',
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'scipy',
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@ -183,11 +183,10 @@ class TestBasic(unittest.TestCase):
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assert dm.num_col() == 2
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assert dm.num_col() == 2
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def test_load_file_invalid(self):
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def test_load_file_invalid(self):
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self.assertRaises(xgb.core.XGBoostError, xgb.Booster,
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self.assertRaises(ValueError, xgb.Booster,
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model_file='incorrect_path')
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model_file='incorrect_path')
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self.assertRaises(ValueError, xgb.Booster,
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self.assertRaises(xgb.core.XGBoostError, xgb.Booster,
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model_file=u'不正なパス')
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model_file=u'不正なパス')
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def test_dmatrix_numpy_init(self):
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def test_dmatrix_numpy_init(self):
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