Leandro Ferrado
Leandro Ferrado
Assert correct behavior of OSELMClassifier in sequential learning scenarios with feed of new classes
Let's say the model was trained with classes 1-N, and then a batch of data comes to a fit() call with a new class N+1. The model should incorporate this...
This library could have a new feature: a module `optimization` with methods to try different hyper-parameters settings to get the best configuration of a model for a given dataset X,...
In order to increase the learning capacity of a model, it would be convenient to think in architectures of multiple layers. Check this paper: https://www.hindawi.com/journals/mpe/2017/4670187/
All the calls to `pinv2` function could raise errors if a singular matrix is operated. We could either identify these cases or just try/catch them to raise a proper error...
This PR is intended to solve #88 by updating the dependencies and corresponding code & config.
* SteganoGAN version or git commit: `master` 513912f3dce2fb5001f3e140ad7378dacfc2a453 * Python version (output of `python --version`): `Python 3.8.10` * Pip version (output of `pip --version`): `pip 23.0` * PyTorch version (output...