GH-15780 set weak learner parameter api documentation #15920
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maurever
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|
@hannah-tillman can you please check the wording? |
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| @@ -49,6 +49,10 @@ Algorithm-specific parameters | |||
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| - ``GLM``: Trains a binary classifier with ``max_iterations=50``. | |||
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| - ``DEEP_LEARNING``: Trains a binary classifier with ``(epochs=10, hidden=[2])``. | |||
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| - **weak_learner_params**: With ``weak_learner``, you can also specify a dict/list of customized parameters for that algorithm. For example if we use a ``GBM``, we can specify ``{'ntrees': 1, 'max_depth': 10}`` in Python and ``list(ntrees = 1, max_depth = 10)`` in R. AdaBoost does not apply defaults from the ``weak_learner`` at all. The defaults of the algorithm itself will be used instead. | |||
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| - **weak_learner_params**: With ``weak_learner``, you can also specify a dict/list of customized parameters for that algorithm. For example if we use a ``GBM``, we can specify ``{'ntrees': 1, 'max_depth': 10}`` in Python and ``list(ntrees = 1, max_depth = 10)`` in R. AdaBoost does not apply defaults from the ``weak_learner`` at all. The defaults of the algorithm itself will be used instead. | |
| - **weak_learner_params**: You can specify a dict/list of customized parameters for your specified ``weak_learner`` algorithm. For example, if you use a ``GBM``, you can specify ``{'ntrees': 1, 'max_depth': 10}`` in Python or ``list(ntrees = 1, max_depth = 10)`` in R. AdaBoost does not apply defaults from the ``weak_learner`` at all. The defaults of the algorithm itself will be used instead. |
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#15780