Make Machine class stateless #5111
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Nice to see this coming in :) |
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@LiuYuHui sorry for the delays, I was meant to do this a while ago. I rebased your branch now and it should be good to merge soon. Feel free to review in case I messed up the rebase |
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gf712
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Dec 8, 2020
| @@ -78,7 +78,7 @@ namespace shogun | |||
| }, v.second); | |||
| } | |||
| m_ensemble_machine->train(current_data, labs); | |||
| return m_ensemble_machine; | |||
| return true; | |||
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@LiuYuHui I had to change the return type, since that is the type of Machine::train. In future it might be worth returning the Machine object.
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| machine->train(train_feats, train_labels); | ||
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| auto pred = machine->apply_multiclass(test_feats); |
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At some point Machines should return a pointer to themselves after calling train (like in sklearn) so that we can use a builder pattern in situations like this
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* add nonparametric machine * fix notebooks
* refactor gp machine
* Refactor KernelMachine
* refactor linear machine * fix unit tests * update gpl submodule * use DotFeatures in train_machine
* Refactor Multiclass Machine
* Add NonParametricMachine class (#5055) * add nonparametric machine * fix notebooks * Refactor NearestCentroid class
* make BaggingMachine stateless * change get_oob_error to lambda * fix meta example * fix segfault
* refactor all machines * fix unit test * fix python legacy and jupyter notebook
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@LiuYuHui's main GSoC project. Machine class becomes stateless wrt Features and Labels which means that the user has to provide features and labels when fitting a Machine. This is essentially done by adding the notion of (Non)Parametric Machines.