@@ -505,6 +505,9 @@ class PLSRegression(_PLS):
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PLSRegression is also known as PLS2 or PLS1, depending on the number of
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targets.
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+ For a comparison between other cross decomposition algorithms, see
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+ :ref:`sphx_glr_auto_examples_cross_decomposition_plot_compare_cross_decomposition.py`.
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Read more in the :ref:`User Guide <cross_decomposition>`.
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.. versionadded:: 0.8
@@ -596,6 +599,9 @@ class PLSRegression(_PLS):
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>>> pls2.fit(X, Y)
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PLSRegression()
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>>> Y_pred = pls2.predict(X)
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+ For a comparison between PLS Regression and :class:`~sklearn.decomposition.PCA`, see
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+ :ref:`sphx_glr_auto_examples_cross_decomposition_plot_pcr_vs_pls.py`.
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"""
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_parameter_constraints : dict = {** _PLS ._parameter_constraints }
@@ -650,6 +656,9 @@ def fit(self, X, Y):
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class PLSCanonical (_PLS ):
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"""Partial Least Squares transformer and regressor.
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+ For a comparison between other cross decomposition algorithms, see
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+ :ref:`sphx_glr_auto_examples_cross_decomposition_plot_compare_cross_decomposition.py`.
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Read more in the :ref:`User Guide <cross_decomposition>`.
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.. versionadded:: 0.8
@@ -780,6 +789,9 @@ def __init__(
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class CCA (_PLS ):
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"""Canonical Correlation Analysis, also known as "Mode B" PLS.
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+ For a comparison between other cross decomposition algorithms, see
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+ :ref:`sphx_glr_auto_examples_cross_decomposition_plot_compare_cross_decomposition.py`.
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Read more in the :ref:`User Guide <cross_decomposition>`.
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Parameters
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