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[DOC,MNT] Documentation configuration clean-up (#2911)
* start * remove old parameter * numpydoc config * conf tidy * headers * exclude unused methods and update gsoc in about * changelog * binder button * myst config * remove extra bullet point * changelog * Automatic `pre-commit` fixes --------- Co-authored-by: MatthewMiddlehurst <25731235+MatthewMiddlehurst@users.noreply.github.com>
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aeon/classification/deep_learning/base.py

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@@ -49,10 +49,9 @@ class BaseDeepClassifier(BaseClassifier):
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The name of the file of the last model, used
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only if save_last_model_to_file is used
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Arguments
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---------
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Attributes
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----------
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self.model = None
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"""
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_tags = {

aeon/networks/_ae_abgru.py

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def build_network(self, input_shape, **kwargs):
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"""Construct a network and return its input and output layers.
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---------
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Parameters
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----------
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input_shape : tuple of shape = (n_timepoints (m), n_channels (d))
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The shape of the data fed into the input layer.
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kwargs : dict

aeon/networks/_ae_dcnn.py

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def build_network(self, input_shape):
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"""Construct a network and return its input and output layers.
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----------
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input_shape : tuple of shape = (n_timepoints (m), n_channels (d))
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The shape of the data fed into the input layer.
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docs/_templates/class_with_call.rst

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docs/about.md

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- GitHub ID
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- Organization
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- Year
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* - Balgopal Moharana
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- {user}`lucifer4073`
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- [Google Summer of Code](https://summerofcode.withgoogle.com)
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- 2025
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* - Jiarong Jin
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- {user}`TinaJin0228`
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- [Google Summer of Code](https://summerofcode.withgoogle.com)
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- 2025
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* - Divya Tiwari
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- {user}`itsdivya1309`
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- [Google Summer of Code](https://summerofcode.withgoogle.com)

docs/changelogs/v1.2.md

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## Highlights
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- `aeon` v1.2.0 drops support for Python 3.9, Python 3.10-3.13 are the current supported versions.
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- `aeon` v1.2.0 drops support for Python 3.9, Python 3.10-3.13 are the currently supported versions.
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- Framework for whole-series anomaly detection has been implemented, and the module has been refactored
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into `anomaly_detection.collection` and `anomaly_detection.series` submodules.
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- `ProximityForect` and `ProximityTree` classifiers have been improved to support
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- `ProximityForest` and `ProximityTree` classifiers have been improved to support
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unequal length and multivariate series. The classifiers are also significantly faster.
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- A new implementation for the `TD-MVDC` classifier
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- The forecasting module has been enhanced with additional methods for direct and recursive forecasting,
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as well as new algorithms such as ETS. This module is still in early development, and we expect
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framework changes in future releases.
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- The similarity search module has been significantly reworked to fit the `aeon` style
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framework seen in other modules. See the module examples and documentation for more details.
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- The start of a sub-package for self suprervised learning has been added in
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- The start of an experimental sub-package for self supervised learning has been added in
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`aeon.transformations.collection.self_supervised`, starting with the `TRILITE` algorithm.
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## Anomaly Detection

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