Text preprocessing V2 TODOs

[mfeurer]

This is a list of follow-up tasks to #1300.

General implementation

• [x] Improve text example to include more meaningful dataset
• [x] Improve text example to contain links to further material that describes how we handle text data, for example this
• [x] Rename hyperparameters following this comment
• [x] Potentially move the text feature reduction to a different module
• [x] discuss handling of pandas dtype object -> can we default it to string or categorical?
• [x] Add a parameter to allow for text processing (default to True)
• [x] Discuss text feature support in the manual
• [x] Improve the way feature types are passed to the meta-feature computation (search for the following todo: Todo make this more cohesive to the overall structure (quick bug fix))
• [x] Fix https://github.com/automl/auto-sklearn/issues/741

Hyperparameter space

• [ ] Benchmark whether TF/IDF should be applied on a per-sample or per-feature level (see https://github.com/automl/auto-sklearn/pull/1300#discussion_r787863150)
• [ ] Improve text feature reduction upper and lower bound

[Louquinze]

can not find Improve the way feature types are passed to the meta-feature computation (search for the following todo: Todo make this more cohesive to the overall structure (quick bug fix)) in the open to do's

edit: metafeatures.py:1089

[mfeurer]

I think the comment right now says: TODO make this more cohesive to the overall structure (quick bug fix)

[Louquinze]

can we rename the point "Potentially move the text feature reduction to a different module" to "Potentially rename the text feature reduction to a different module" ?

[mfeurer]

Sure