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[PYTHON] Simplify training logic, update rabit lib

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tqchen
2016-02-27 19:56:29 -08:00
parent 90bc7f8f6b
commit 4a16b729fc
10 changed files with 108 additions and 77 deletions
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4
tests/python/test_models.py
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@@ -31,7 +31,7 @@ class TestModels(unittest.TestCase):
# learning_rates as a customized decay function
def eta_decay(ithround, num_boost_round):
return num_boost_round / ithround
return num_boost_round / (ithround + 1)
bst = xgb.train(param, dtrain, num_round, watchlist, learning_rates=eta_decay)
assert isinstance(bst, xgb.core.Booster)
@@ -49,7 +49,7 @@ class TestModels(unittest.TestCase):
def evalerror(preds, dtrain):
labels = dtrain.get_label()
return 'error', float(sum(labels != (preds > 0.0))) / len(labels)
# test custom_objective in training
bst = xgb.train(param, dtrain, num_round, watchlist, logregobj, evalerror)
assert isinstance(bst, xgb.core.Booster)