使用xgboost訓練多分類模型時遇到問題。

參數(shù)配置如下：

xgb_params = {
    "eta": 0.1,
    "seed": 0,
    "colsample_bytree": 0.8,
    "silent": 0,
    "subsample": 1,
    # "objective": "multi:softmax",
    "num_class": 8477,
    "max_depth": 6,
    "min_child_weight": 1,
    "eval_metric": "merror",
    "lambda": 1,
}
watchlist = [(dtrain, "train"), (dtest, "test")]
model = xgb.train(xgb_params, dtrain, num_boost_round=100, evals=watchlist, obj="multi:softmax")

錯誤提示信息：

File "D:\Anaconda2\lib\site-packages\xgboost-0.4-py2.7.egg\xgboost\training.py", line 121, in train
    bst.update(dtrain, i, obj)
File "D:\Anaconda2\lib\site-packages\xgboost-0.4-py2.7.egg\xgboost\core.py", line 696, in update
    pred = self.predict(dtrain)
File "D:\Anaconda2\lib\site-packages\xgboost-0.4-py2.7.egg\xgboost\core.py", line 838, in predict
    ctypes.byref(preds)))
File "D:\Anaconda2\lib\site-packages\xgboost-0.4-py2.7.egg\xgboost\core.py", line 97, in _check_call
    raise XGBoostError(_LIB.XGBGetLastError())
xgboost.core.XGBoostError: bad allocation

運行時情況：
內(nèi)存使用率在25%左右