XGBoost plot importance has no property max_num_features

Question

xgboost's plotting API states:

xgboost.plot_importance(booster, ax=None, height=0.2, xlim=None, ylim=None, title='Feature importance', xlabel='F score', ylabel='Features', importance_type='weight', max_num_features=None, grid=True, **kwargs)¶

Plot importance based on fitted trees.

Parameters:

booster (Booster, XGBModel or dict) – Booster or XGBModel instance, or dict taken by Booster.get_fscore()
...
max_num_features (int, default None) – Maximum number of top features displayed on plot. If None, all features will be displayed.

In my implementation, however, running:

booster_ = XGBClassifier(learning_rate=0.1, max_depth=3, n_estimators=100, 
                      silent=False, objective='binary:logistic', nthread=-1, 
                      gamma=0, min_child_weight=1, max_delta_step=0, subsample=1, 
                      colsample_bytree=1, colsample_bylevel=1, reg_alpha=0,
                      reg_lambda=1, scale_pos_weight=1, base_score=0.5, seed=0)

booster_.fit(X_train, y_train)

from xgboost import plot_importance
plot_importance(booster_, max_num_features=10)

Returns:

AttributeError: Unknown property max_num_features

While running it without the parameter max_num_features plots correctly the entire feature set (which in my case is gigantic, ~10k features). Any ideas of what's going on?

Thanks in advance.

Details:

> python -V
  Python 2.7.12 :: Anaconda custom (x86_64)

> pip freeze | grep xgboost
  xgboost==0.4a30

Answer 1

Try to upgrade your xgboost library to 0.6. It should solve the problem. To upgrade the package, try this:

$ pip install -U xgboost

If you get an error, try this:

$ brew install gcc@5
$ pip install -U xgboost

(Refer to this https://github.com/dmlc/xgboost/issues/1501)