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[ENH] Add and Validate n_layers, n_units, activation & dropout_rate kwargs to MLPNetwork #2338

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[ENH] Add and Validate n_layers, n_units, activation & dropout_rate kwargs to MLPNetwork #2338

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Closes #2337 .

@aeon-actions-bot aeon-actions-bot bot added enhancement New feature, improvement request or other non-bug code enhancement networks Networks package labels Nov 11, 2024
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Thank you for contributing to aeon

I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ].
I have added the following labels to this PR based on the changes made: [ $\color{#379E11}{\textsf{networks}}$ ]. Feel free to change these if they do not properly represent the PR.

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@aadya940 aadya940 added the deep learning Deep learning related label Nov 11, 2024
hadifawaz1999
hadifawaz1999 requested changes Nov 11, 2024
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Thx for taking care of it.
In general:

  • All parameters should be defined as private in constructor before starting anything
  • the assertions and all the list checking should only be in build_network method not constructor, this will avoid causing issues on CI (check for example how fcn network is implemented)
  • Also given we are parametrizing the network, the associated classifier and regressor should be parametrized as such (also docs) and use them when calling the network
  • I left some other comments to check

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@hadifawaz1999 hadifawaz1999 mentioned this pull request Nov 21, 2024
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@hadifawaz1999 hadifawaz1999 hadifawaz1999 requested changes

@MatthewMiddlehurst MatthewMiddlehurst Awaiting requested review from MatthewMiddlehurst MatthewMiddlehurst is a code owner

@TonyBagnall TonyBagnall Awaiting requested review from TonyBagnall TonyBagnall is a code owner

@dguijo dguijo Awaiting requested review from dguijo dguijo is a code owner

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[ENH] Parametrize MLP Network, classifier and regressor
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