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Feb 22, 2024
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DOC add links to neural network examples #26935

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d8c921d
docs(neural_networks): add links to neural network examples
punndcoder28 Jul 29, 2023
6fa7dd8
fix: add comment for mlp weight viz, move rbm example to examples sec…
punndcoder28 Aug 2, 2023
ba83e7f
fix: moving links for examples to approriate section
punndcoder28 Aug 16, 2023
69b5bac
fix: fix failing lint job
punndcoder28 Aug 16, 2023
29dcff6
refactor: removed redundant links to examples
punndcoder28 Aug 27, 2023
cdbe78f
docs: fixing example message links in mlp
punndcoder28 Aug 29, 2023
f09c077
fix: add missing period for docs
punndcoder28 Jan 6, 2024
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3 changes: 2 additions & 1 deletion doc/modules/neural_networks_supervised.rst
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Expand Up @@ -146,7 +146,8 @@ See the examples below and the docstring of
.. topic:: Examples:

* :ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_training_curves.py`
* :ref:`sphx_glr_auto_examples_neural_networks_plot_mnist_filters.py`
* See :ref:`sphx_glr_auto_examples_neural_networks_plot_mnist_filters.py` for
visualized representation of trained weights.

Regression
==========
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9 changes: 9 additions & 0 deletions sklearn/neural_network/_multilayer_perceptron.py
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Expand Up @@ -800,6 +800,9 @@ class MLPClassifier(ClassifierMixin, BaseMultilayerPerceptron):
- 'adam' refers to a stochastic gradient-based optimizer proposed
by Kingma, Diederik, and Jimmy Ba

For a comparison between Adam optimizer and SGD, see
:ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_training_curves.py`.

Note: The default solver 'adam' works pretty well on relatively
large datasets (with thousands of training samples or more) in terms of
both training time and validation score.
Expand All @@ -810,6 +813,9 @@ class MLPClassifier(ClassifierMixin, BaseMultilayerPerceptron):
Strength of the L2 regularization term. The L2 regularization term
is divided by the sample size when added to the loss.

For an example usage and visualization of varying regularization, see
:ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_alpha.py`.

batch_size : int, default='auto'
Size of minibatches for stochastic optimizers.
If the solver is 'lbfgs', the classifier will not use minibatch.
Expand Down Expand Up @@ -1293,6 +1299,9 @@ class MLPRegressor(RegressorMixin, BaseMultilayerPerceptron):
- 'adam' refers to a stochastic gradient-based optimizer proposed by
Kingma, Diederik, and Jimmy Ba

For a comparison between Adam optimizer and SGD, see
:ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_training_curves.py`.

Note: The default solver 'adam' works pretty well on relatively
large datasets (with thousands of training samples or more) in terms of
both training time and validation score.
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3 changes: 3 additions & 0 deletions sklearn/neural_network/_rbm.py
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Expand Up @@ -127,6 +127,9 @@ class BernoulliRBM(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstima
>>> model = BernoulliRBM(n_components=2)
>>> model.fit(X)
BernoulliRBM(n_components=2)

For a more detailed example usage, see
:ref:`sphx_glr_auto_examples_neural_networks_plot_rbm_logistic_classification.py`.
"""

_parameter_constraints: dict = {
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