Comments (6)
I set 'bst:gamma': 0.0
in case that matters
from xgboost.
hmm.. can you post a script that can produces the error? I can't produce this error with my script.
#!/usr/bin/python
import sys
import sklearn.datasets
sys.path.append('../')
import xgboost as xgb
x, y = sklearn.datasets.make_hastie_10_2()
y[y==-1] = 0
dtrain = xgb.DMatrix(x, label=y)
param = {'bst:max_depth':2, 'bst:eta':1, 'bst:gamma':0, 'objective':'binary:logistic', 'silent':1 }
num_round = 10
evallist = [(dtrain,'train')]
bst = xgb.train( param, dtrain, num_round, evallist )
from xgboost.
this is strange: I fail to create an isolated script to reproduce it. Even stranger: the error only occurs if I run either Rgbm (via rpy2) or sklearn's GradientBoostingClassifier before... but in this case its 100% reproducible. BTW: it happens in bst.predict
not xgb.train
from xgboost.
i have some idea what happened.
This can due to the fact that we are using pointer to check if a matrix a cached. If a matrix get freed and another allocation gets the same address, we can run into trouble.
There is a update in dev branch that fixed this problem, but we would like to test before we release it
from xgboost.
checked with the dev branch - you fixed it!
from xgboost.
Thanks peter! Indeed this is a problem that we overlooked:)
from xgboost.
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from xgboost.