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Dec 3, 2022
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DOC fix some typo in miscellaneous.rst #893

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2bde738
edit typos in miscellaneous.rst
nada-adel-mohamady Feb 16, 2022
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glemaitre Mar 16, 2022
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9 changes: 5 additions & 4 deletions doc/miscellaneous.rst
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Expand Up @@ -34,7 +34,7 @@ to retain the 10 first elements of the array ``X`` and ``y``::
>>> np.all(y_res == y[:10])
True

In addition, the parameter ``validate`` control input checking. For instance,
In addition, the parameter ``validate`` controls input checking. For instance,
turning ``validate=False`` allows to pass any type of target ``y`` and do some
sampling for regression targets::

Expand All @@ -51,7 +51,7 @@ sampling for regression targets::
75.46571114, -67.49177372, 159.72700509, -169.80498923,
211.95889757, 211.95889757])

We illustrate the use of such sampler to implement an outlier rejection
We illustrated the use of such sampler to implement an outlier rejection
estimator which can be easily used within a
:class:`~imblearn.pipeline.Pipeline`:
:ref:`sphx_glr_auto_examples_applications_plot_outlier_rejections.py`
Expand All @@ -69,10 +69,11 @@ will generate balanced mini-batches.
TensorFlow generator
~~~~~~~~~~~~~~~~~~~~

The :func:`~imblearn.tensorflow.balanced_batch_generator` allow to generate
The :func:`~imblearn.tensorflow.balanced_batch_generator` allows to generate
balanced mini-batches using an imbalanced-learn sampler which returns indices.

Let's first generate some data::

>>> n_features, n_classes = 10, 2
>>> X, y = make_classification(
... n_samples=10_000, n_features=n_features, n_informative=2,
Expand All @@ -96,7 +97,7 @@ balanced::
... random_state=42,
... )

The ``generator`` and ``steps_per_epoch`` is used during the training of the
The ``generator`` and ``steps_per_epoch`` are used during the training of a
Tensorflow model. We will illustrate how to use this generator. First, we can
define a logistic regression model which will be optimized by a gradient
descent::
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