update docs for parameters (#9900)
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@ -78,7 +78,7 @@ Parameters for Tree Booster
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* ``gamma`` [default=0, alias: ``min_split_loss``]
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- Minimum loss reduction required to make a further partition on a leaf node of the tree. The larger ``gamma`` is, the more conservative the algorithm will be.
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- Minimum loss reduction required to make a further partition on a leaf node of the tree. The larger ``gamma`` is, the more conservative the algorithm will be. Note that a tree where no splits were made might still contain a single terminal node with a non-zero score.
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- range: [0,∞]
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* ``max_depth`` [default=6]
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@ -388,6 +388,7 @@ Specify the learning task and the corresponding learning objective. The objectiv
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- The initial prediction score of all instances, global bias
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- The parameter is automatically estimated for selected objectives before training. To
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disable the estimation, specify a real number argument.
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- If ``base_margin`` is supplied, ``base_score`` will not be added.
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- For sufficient number of iterations, changing this value will not have too much effect.
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* ``eval_metric`` [default according to objective]
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