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当我尝试使用以下代码时出现以下错误。

******代码******

    importance = bst.get_fscore(fmap='xgb.fmap')
    importance = sorted(importance.items(), key=operator.itemgetter(1))

******错误******

  File "scripts/xgboost_bnp.py", line 225, in <module>
  importance = bst.get_fscore(fmap='xgb.fmap')
  File "/usr/lib/python2.7/site-packages/xgboost/core.py", line 754, in get_fscore
    trees = self.get_dump(fmap)
  File "/usr/lib/python2.7/site-packages/xgboost/core.py", line 740, in get_dump
   ctypes.byref(sarr)))
  File "/usr/lib/python2.7/site-packages/xgboost/core.py", line 92, in _check_call
raise XGBoostError(_LIB.XGBGetLastError())
xgboost.core.XGBoostError: can not open file "xgb.fmap"
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1 回答 1

5

引发错误是因为您get_fscore使用可选参数进行调用，该参数fmap说明每个特征的特征重要性应从名为 的特征映射文件中获取xgb.fmap，该文件系统中不存在该文件。

这是一个返回排序特征名称及其重要性的函数：

import xgboost as xgb
import pandas as pd

def get_xgb_feat_importances(clf):

    if isinstance(clf, xgb.XGBModel):
        # clf has been created by calling
        # xgb.XGBClassifier.fit() or xgb.XGBRegressor().fit()
        fscore = clf.booster().get_fscore()
    else:
        # clf has been created by calling xgb.train.
        # Thus, clf is an instance of xgb.Booster.
        fscore = clf.get_fscore()

    feat_importances = []
    for ft, score in fscore.iteritems():
        feat_importances.append({'Feature': ft, 'Importance': score})
    feat_importances = pd.DataFrame(feat_importances)
    feat_importances = feat_importances.sort_values(
        by='Importance', ascending=False).reset_index(drop=True)
    # Divide the importances by the sum of all importances
    # to get relative importances. By using relative importances
    # the sum of all importances will equal to 1, i.e.,
    # np.sum(feat_importances['importance']) == 1
    feat_importances['Importance'] /= feat_importances['Importance'].sum()
    # Print the most important features and their importances
    print feat_importances.head()
    return feat_importances
于 2016-03-20T10:53:22.290 回答