8000 Allow the creation of a pipeline for non-parametric functions like TSNE by cathelineparisot · Pull Request #22162 · scikit-learn/scikit-learn · GitHub
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Allow the creation of a pipeline for non-parametric functions like TSNE #22162

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Allow the creation of a pipeline for non-parametric functions like TSNE #22162

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3b294b2
[fix]allow-when-only-fit-transform
cathelineparisot Jan 10, 2022
0a6edc9
Try to fix linting pb
cathelineparisot Jan 10, 2022
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2 changes: 1 addition & 1 deletion doc/modules/manifold.rst
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Expand Up @@ -417,7 +417,7 @@ version, the algorithms will try to preserve the order of the distances, and
hence seek for a monotonic relationship between the distances in the embedded
space and the similarities/dissimilarities.

.. figure:: ../auto_examples/manifold/images/sphx_glr_plot_lle_digits_010.png
.. figure:: ../auto_examples/manifold/images/sphx_glr_plot_lle_digits_002.png
:target: ../auto_examples/manifold/plot_lle_digits.html
:align: center
:scale: 50
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18 changes: 7 additions & 11 deletions sklearn/pipeline.py
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Expand Up @@ -201,15 +201,12 @@ def _validate_steps(self):
for t in transformers:
if t is None or t == "passthrough":
continue
if not (hasattr(t, "fit") or hasattr(t, "fit_transform")) or not hasattr(
t, "transform"
):
raise TypeError(
"All intermediate steps should be "
"transformers and implement fit and transform "
"or be the string 'passthrough' "
"'%s' (type %s) doesn't" % (t, type(t))
)
if (not (hasattr(t, "fit") or hasattr(t, "fit_transform")) or not
hasattr(t, "transform")):
raise TypeError("All intermediate steps should be "
"transformers and implement fit and transform "
"or be the string 'passthrough' "
"'%s' (type %s) doesn't" % (t, type(t)))

# We allow last estimator to be None as an identity transformation
if (
Expand All @@ -220,8 +217,7 @@ def _validate_steps(self):
raise TypeError(
"Last step of Pipeline should implement fit "
"or be the string 'passthrough'. "
"'%s' (type %s) doesn't" % (estimator, type(estimator))
)
"'%s' (type %s) doesn't" % (estimator, type(estimator)))

def _iter(self, with_final=True, filter_passthrough=True):
"""
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