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sinhrks
2016-04-24 16:34:46 +09:00
parent b3c9e6a0db
commit 8fc2456c87
19 changed files with 282 additions and 199 deletions
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38
tests/python/test_with_pandas.py
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@@ -111,43 +111,55 @@ class TestPandas(unittest.TestCase):
u'train-error-mean', u'train-error-std'])
assert cv.columns.equals(exp)
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic', 'eval_metric': 'auc'}
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic', 'eval_metric': 'auc'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True)
assert 'eval_metric' in params
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic', 'eval_metric': ['auc']}
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True)
assert 'eval_metric' in params
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, early_stopping_rounds=1)
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, early_stopping_rounds=1)
assert 'eval_metric' in params
assert 'auc' in cv.columns[0]
assert cv.shape[0] < 10
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, metrics='auc')
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics='auc')
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, metrics=['auc'])
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics=['auc'])
assert 'auc' in cv.columns[0]
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, metrics='error')
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic', 'eval_metric': ['auc']}
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics='error')
assert 'eval_metric' in params
assert 'auc' not in cv.columns[0]
assert 'error' in cv.columns[0]
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, metrics=['error'])
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics=['error'])
assert 'eval_metric' in params
assert 'auc' not in cv.columns[0]
assert 'error' in cv.columns[0]
params = list(params.items())
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=True, metrics=['error'])
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10,
as_pandas=True, metrics=['error'])
assert isinstance(params, list)
assert 'auc' not in cv.columns[0]
assert 'error' in cv.columns[0]
assert 'error' in cv.columns[0]