我使用 Scikit-Learn Python API 在 Python 中训练了一个 xgboost 模型,并使用 pickle
对其进行了序列化。图书馆。我将模型上传到 ML Engine,但是当我尝试进行在线预测时,出现以下异常:
Prediction failed: Exception during xgboost prediction: can not initialize DMatrix from DMatrix
我用于预测的 json 示例如下:
{
"instances":[
[
24.90625,
21.6435643564356,
20.3762376237624,
24.3679245283019,
30.2075471698113,
28.0947368421053,
16.7797359774725,
14.9262079299572,
17.9888028979966,
15.3333284503293,
19.6535308744024,
17.1501961307627,
0.0,
0.0,
0.0,
0.0,
0.0,
509.0,
497.0,
439.0,
427.0,
407.0,
1.0,
1.0,
1.0,
1.0,
1.0,
2.0,
23.0,
10.0,
58.0,
11.0,
20.0,
23.3617021276596,
23.3617021276596,
23.3617021276596,
23.3617021276596,
23.3617021276596,
23.9423076923077,
26.3082269243683,
23.6212606363851,
22.6752334301282,
27.4343583104833,
34.0090408101173,
11.1991944104063,
7.33420726455092,
8.15160392948917,
11.4119236389594,
17.9429092915607,
18.0573102225845,
32.8902876598084,
-0.00286123032904149,
-0.00286123032904149,
-0.00286123032904149,
-0.00286123032904149,
-0.00286123032904149,
-0.0028328611898017,
0.0534138904223018,
0.0534138904223018,
0.0534138904223018,
0.0534138904223018,
0.0534138904223018,
0.0531491870801522
]
]
}
我使用以下代码来训练我的模型:
def _train_model(X, y):
clf = xgb.XGBClassifier(max_depth=6,
learning_rate=0.01,
n_estimators=100,
n_jobs=-1)
clf.fit(X, y)
return clf
哪里
X
和 y
都是 numpy.ndarray
:Type of X: <class 'numpy.ndarray'> Type of y: <class 'numpy.ndarray'>
我也在使用
xgboost 0.72.1
, Python 3.5
和 ML 运行时 1.9
.任何人都知道问题的根源是什么?
谢谢!
最佳答案
似乎问题是由于酸洗造成的。我能够重现它并进行修复,但与此同时,您可以尝试像下面这样导出分类器吗?
clf._Booster.save_model('./model.bst')
那应该暂时解除对您的阻止。如果没有,请随时联系
cloudml-feedback@google.com
.
关于python-3.x - xgboost 预测期间的异常 : can not initialize DMatrix from DMatrix,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53506997/