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Updated the documentation a bit

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Will upload some demos for guide-python later.
This commit is contained in:
Johan Manders 2015-10-14 12:53:42 +02:00
parent e960a09ff4
commit 9c8420a4dc
1 changed files with 4 additions and 1 deletions
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python-package/xgboost/training.py
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@ -38,7 +38,10 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
If early stopping occurs, the model will have two additional fields: If early stopping occurs, the model will have two additional fields:
bst.best_score and bst.best_iteration. bst.best_score and bst.best_iteration.
evals_result: dict evals_result: dict
This dictionary stores the evaluation results of all the items in watchlist This dictionary stores the evaluation results of all the items in watchlist.
Example: with a watchlist containing [(dtest,'eval'), (dtrain,'train')] and
and a paramater containing ('eval_metric', 'logloss')
Returns: {'train': {'logloss': ['0.48253', '0.35953']}, 'eval': {'logloss': ['0.480385', '0.357756']}}
verbose_eval : bool verbose_eval : bool
If `verbose_eval` then the evaluation metric on the validation set, if If `verbose_eval` then the evaluation metric on the validation set, if
given, is printed at each boosting stage. given, is printed at each boosting stage.