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[docs] clarify that custom eval functions are not only used on training data #5011

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Feb 17, 2022
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[docs] clarify that custom eval functions are not only used on training data #5011

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2 changes: 1 addition & 1 deletion python-package/lightgbm/basic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3151,7 +3151,7 @@ def eval(self, data, name, feval=None):
If ``fobj`` is specified, predicted values are returned before any transformation,
e.g. they are raw margin instead of probability of positive class for binary task in this case.
eval_data : Dataset
The evaluation dataset.
A ``Dataset`` to evaluate.
eval_name : str
The name of evaluation function (without whitespace).
eval_result : float
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8 changes: 4 additions & 4 deletions python-package/lightgbm/engine.py
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Expand Up @@ -83,7 +83,7 @@ def train(
If ``fobj`` is specified, predicted values are returned before any transformation,
e.g. they are raw margin instead of probability of positive class for binary task in this case.
eval_data : Dataset
The training dataset.
A ``Dataset`` to evaluate.
eval_name : str
The name of evaluation function (without whitespaces).
eval_result : float
Expand Down Expand Up @@ -429,15 +429,15 @@ def cv(params, train_set, num_boost_round=100,

feval : callable, list of callable, or None, optional (default=None)
Customized evaluation function.
Each evaluation function should accept two parameters: preds, train_data,
Each evaluation function should accept two parameters: preds, eval_data,
and return (eval_name, eval_result, is_higher_better) or list of such tuples.

preds : numpy 1-D array
The predicted values.
If ``fobj`` is specified, predicted values are returned before any transformation,
e.g. they are raw margin instead of probability of positive class for binary task in this case.
train_data : Dataset
The training dataset.
eval_data : Dataset
A ``Dataset`` to evaluate.
eval_name : str
The name of evaluation function (without whitespace).
eval_result : float
Expand Down