Validation data generation, removal of loss function overrides

[kaueltzen]

Resolves #228 .

Overview

• Replaces train_test_split with explicit generation of validation data that is reproducible, shuffled and stratified (if classification tasks are present)
  • as in #232 no explicit determination of classification targets for stratification, uses first target instead
• Removes override of loss function for classification tasks in fit of MODNetModel

[kaueltzen]

Hi @ppdebreuck I have a question regarding this comment: https://github.com/ppdebreuck/modnet/issues/228#issuecomment-2437540148

Do you think it would make sense to enable the passing of a loss function for classification tasks in evaluate of MODNetModel? Or would you prefer keeping -ROC-AUC (e.g., because it's easier to interpret than cross entropy losses)?

[ppdebreuck]

Hi @ppdebreuck I have a question regarding this comment: #228 (comment)

Do you think it would make sense to enable the passing of a loss function for classification tasks in evaluate of MODNetModel? Or would you prefer keeping -ROC-AUC (e.g., because it's easier to interpret than cross entropy losses)?

No problem with me, as you can put ROC_AUC as default metric to keep current behavior, while adding flexibility if you need to change it :) (I would put it in a separate PR)