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Add additional Python tests to test training under constraints (#4426)

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This commit is contained in:
Philip Hyunsu Cho
2019-04-30 18:23:39 -07:00
committed by GitHub
parent eaab364a63
commit ba98e0cdf2
3 changed files with 44 additions and 3 deletions
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19
tests/python/test_monotone_constraints.py
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@@ -1,7 +1,9 @@
import numpy as np
import xgboost as xgb
import unittest
from sklearn.metrics import accuracy_score
dpath = 'demo/data/'
def is_increasing(y):
return np.count_nonzero(np.diff(y) < 0.0) == 0
@@ -97,3 +99,20 @@ class TestMonotoneConstraints(unittest.TestCase):
)
assert is_correctly_constrained(constrained_hist_method)
def test_training_accuracy(self):
dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train?indexing_mode=1')
dtest = xgb.DMatrix(dpath + 'agaricus.txt.test?indexing_mode=1')
params = {'eta': 1, 'max_depth': 6, 'objective': 'binary:logistic',
'tree_method': 'hist', 'monotone_constraints': '(1, 0)'}
num_boost_round = 5
params['grow_policy'] = 'lossguide'
bst = xgb.train(params, dtrain, num_boost_round)
pred_dtest = (bst.predict(dtest) < 0.5)
assert accuracy_score(dtest.get_label(), pred_dtest) < 0.1
params['grow_policy'] = 'depthwise'
bst = xgb.train(params, dtrain, num_boost_round)
pred_dtest = (bst.predict(dtest) < 0.5)
assert accuracy_score(dtest.get_label(), pred_dtest) < 0.1