Updated the documentation a bit
Will upload some demos for guide-python later.
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@ -38,7 +38,10 @@ def train(params, dtrain, num_boost_round=10, evals=(), obj=None, feval=None,
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If early stopping occurs, the model will have two additional fields:
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bst.best_score and bst.best_iteration.
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evals_result: dict
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This dictionary stores the evaluation results of all the items in watchlist
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This dictionary stores the evaluation results of all the items in watchlist.
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Example: with a watchlist containing [(dtest,'eval'), (dtrain,'train')] and
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and a paramater containing ('eval_metric', 'logloss')
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Returns: {'train': {'logloss': ['0.48253', '0.35953']}, 'eval': {'logloss': ['0.480385', '0.357756']}}
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verbose_eval : bool
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If `verbose_eval` then the evaluation metric on the validation set, if
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given, is printed at each boosting stage.
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