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[docs] fixed params description #2306

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Aug 4, 2019
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[docs] fixed params description #2306

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fixed params description
StrikerRUS Aug 2, 2019
f529b4c
Merge branch 'master' into docs_params
StrikerRUS Aug 4, 2019
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6 changes: 3 additions & 3 deletions docs/Parameters.rst
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Expand Up @@ -730,7 +730,7 @@ Objective Parameters

- ``is_unbalance`` :raw-html:`<a id="is_unbalance" title="Permalink to this parameter" href="#is_unbalance">&#x1F517;&#xFE0E;</a>`, default = ``false``, type = bool, aliases: ``unbalance``, ``unbalanced_sets``

- used only in ``binary`` and ``multiclassova``
- used only in ``binary`` and ``multiclassova`` applications

- set this to ``true`` if training data are unbalanced

Expand All @@ -740,7 +740,7 @@ Objective Parameters

- ``scale_pos_weight`` :raw-html:`<a id="scale_pos_weight" title="Permalink to this parameter" href="#scale_pos_weight">&#x1F517;&#xFE0E;</a>`, default = ``1.0``, type = double, constraints: ``scale_pos_weight > 0.0``

- used only in ``binary`` and ``multiclassova``
- used only in ``binary`` and ``multiclassova`` applications

- weight of labels with positive class

Expand All @@ -756,7 +756,7 @@ Objective Parameters

- ``boost_from_average`` :raw-html:`<a id="boost_from_average" title="Permalink to this parameter" href="#boost_from_average">&#x1F517;&#xFE0E;</a>`, default = ``true``, type = bool

- used only in ``regression``, ``binary`` and ``cross-entropy`` applications
- used only in ``regression``, ``binary``, ``multiclassova`` and ``cross-entropy`` applications

- adjusts initial score to the mean of labels for faster convergence

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6 changes: 3 additions & 3 deletions include/LightGBM/config.h
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Expand Up @@ -663,14 +663,14 @@ struct Config {
int num_class = 1;

// alias = unbalance, unbalanced_sets
// desc = used only in ``binary`` and ``multiclassova``
// desc = used only in ``binary`` and ``multiclassova`` applications
// desc = set this to ``true`` if training data are unbalanced
// desc = **Note**: while enabling this should increase the overall performance metric of your model, it will also result in poor estimates of the individual class probabilities
// desc = **Note**: this parameter cannot be used at the same time with ``scale_pos_weight``, choose only **one** of them
bool is_unbalance = false;

// check = >0.0
// desc = used only in ``binary`` and ``multiclassova``
// desc = used only in ``binary`` and ``multiclassova`` applications
// desc = weight of labels with positive class
// desc = **Note**: while enabling this should increase the overall performance metric of your model, it will also result in poor estimates of the individual class probabilities
// desc = **Note**: this parameter cannot be used at the same time with ``is_unbalance``, choose only **one** of them
Expand All @@ -681,7 +681,7 @@ struct Config {
// desc = parameter for the sigmoid function
double sigmoid = 1.0;

// desc = used only in ``regression``, ``binary`` and ``cross-entropy`` applications
// desc = used only in ``regression``, ``binary``, ``multiclassova`` and ``cross-entropy`` applications
// desc = adjusts initial score to the mean of labels for faster convergence
bool boost_from_average = true;

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