8000 DOC removed algorithm parameter of CCA (#19047) · scikit-learn/scikit-learn@6af03a5 · GitHub
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DOC removed algorithm parameter of CCA (#19047)
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sklearn/cross_decomposition/_pls.py

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@@ -700,14 +700,8 @@ class CCA(_PLS):
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scale : bool, default=True
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Whether to scale `X` and `Y`.
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algorithm : {'nipals', 'svd'}, default='nipals'
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The algorithm used to estimate the first singular vectors of the
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cross-covariance matrix. 'nipals' uses the power method while 'svd'
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will compute the whole SVD.
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max_iter : int, default=500
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the maximum number of iterations of the power method when
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`algorithm='nipals'`. Ignored otherwise.
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the maximum number of iterations of the power method.
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tol : real, default 1e-06
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The tolerance used as convergence criteria in the power method: the
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n_iter_ : list of shape (n_components,)
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Number of iterations of the power method, for each
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component. Empty if `algorithm='svd'`.
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component.
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Examples
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--------

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