Comments (3)
#71 I agree we can remove it, but don't see a need to deprecate.
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Yeah I meant remove
from aeon.
Assumed so but just wanted to check, I think it's a good idea.
from aeon.
Related Issues (20)
- [DOC] Add Raises to docstrings for methods that can raise exceptions HOT 3
- [ENH] Exclude test_load_has_datasets from standard PR run
- [ENH] Check number of channels and timepoints for equal length matches fit/predict for other BaseCollectionEstimator subclasses
- [ENH] Remove redundant checks of n_timepoints in classifiers
- [ENH] Add `class_weight` parameter to classifiers that use sklearn based estimators with testing
- [BUG] MiniRocket transform slower with univariate series than multivariate
- [BUG] CI failure in `test_all_networks_functionality` from `AEBiGRUNetwork`
- [MNT] Remove Reshape layer from Deep Learning Clusterers HOT 1
- [MNT] Add joblib backend option and set default to all parallelized estimators HOT 9
- [ENH] Add the option to turn off all type checking and conversion and go straight to _fit/_predict/_transform HOT 1
- [DOC] Update Partitional clustering notebook
- [DOC] Add examples for QuerySearch in SimilaritySearch HOT 1
- [BUG] Wrong initialization of bounded cost matrix for some elastic distances HOT 6
- [MNT] Some datasets missing in list of data names
- [DOC] Wrong default value for `return_metadata` in `load_forecasting` HOT 1
- [workflow-cache-dependencies] is STALE HOT 1
- [BUG] PyODAdapter only returns decision_scores_ of train-set HOT 1
- [DOC] Transformation notebook
- [DOC] Typo present in getting start guide: Redundant use of 'n_timepoints' HOT 1
- [BUG] Results loader impossible to load Equal length and No missing values dataset results HOT 1
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