#19542 enables bicluster estimators in common test and skips xfail tests that are failing:

• check_estimators_dtypes
• check_fit2d_1sample
• check_fit2d_1feature
• check_estimator_sparse_data
• check_methods_subset_invariance
• check_dont_overwrite_parameters
• check_fit2d_predict1d

Guidelines for contributors who would like to help fix those issues:

• You can trigger the failure by removing the xfail marker for a specific check and then launch the common tests for that specific check using:

  pytest -v -k check_estimators_dtypes sklearn/tests/test_common.py
  

• Take time to familiarize your-self with Biclustering algorithms (seel also Wikipedia on Biclustering to understand how those estimators are specific.
• Feel free to open a small PR for each sub-problem. It's easier to start with a small PR if this is the first time you contribute.
• When opening a PR please share your analysis of the problem in the description of the PR: what is the intention of the check? should it apply to the Bicluster estimators? or should they be considered a legitimate exception to the rule? and if so why?
• If they are an exception, can we use existing estimators tags? Do we need to introduce a new tag?
• Otherwise there is probably something to change in the code of the Bicluster estimators, in which case don't forget to remove the matching XFAIL marker in your PR.