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DOC - Correct a few wording mistakes (skrub-data#1877)
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examples/FIXME/08_join_aggregation_full.py

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@@ -191,9 +191,10 @@ def get_results(model, X_test, y_test, threshold, amount, time_to_fit):
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# Low effort estimator
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# --------------------
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#
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# Next, we use the |TableVectorizer| and a |HGBC| to create a very simple baseline model
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# that uses the sparse dataset directly. Note that due to the large number of high
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# cardinality columns, we can't use an multi-dimensional encoder like the
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# Next, we use the |TableVectorizer| and an |HGBC| to create a very simple
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# baseline model that uses the sparse dataset directly.
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# Note that due to the large number of high
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# cardinality columns, we can't use a multi-dimensional encoder like the
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# |MinHashEncoder|, because the number of columns would then explode.
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#
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# Instead, we encode our categories with a |TargetEncoder|.
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# %%
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# Now that we get a sense of how the |AggJoiner| can help us, we complete this pipeline
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# with a |HGBC| and evaluate our final model.
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# with an |HGBC| and evaluate our final model.
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tic = time()
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agg_join_estimator = make_pipeline(

skrub/_data_ops/_estimator.py

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@@ -709,7 +709,7 @@ def train_test_split(
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split_func=model_selection.train_test_split,
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**split_func_kwargs,
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):
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"""Split an environment into a training an testing environments.
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"""Split an environment into training and testing environments.
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This functionality is exposed to users through the
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``DataOp.skb.train_test_split()`` method. See the corresponding docstring for
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def iter_cv_splits(data_op, environment, *, keep_subsampling=False, cv=KFOLD_5):
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"""Yield splits of an environment into training an testing environments.
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"""Yield splits of an environment into training and testing environments.
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This functionality is exposed to users through the
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``DataOp.skb.iter_cv_splits()`` method. See the corresponding docstring for

skrub/_data_ops/_skrub_namespace.py

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@@ -1777,7 +1777,7 @@ def train_test_split(
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split_func=model_selection.train_test_split,
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**split_func_kwargs,
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):
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"""Split an environment into a training an testing environments.
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"""Split an environment into training and testing environments.
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Parameters
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----------

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