Comments (4)
For 1.1 I have set the upper bound on scikit learn to 1.2a, to ensure compatibility. Iβm in the process of releasing 1.2 which will use a more modern scikit learn version.
You can build from source on the 1.1.X branch (or the 1.1.1 tag) and change the requirement in pyproject.toml to resolve the error, but itβs not guaranteed that everything works since scikit learn might have made some breaking change in 1.2 that I depend on.
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You would also have to pin the dependency on Cython to 0.29
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This issue has been fixed in 1.1.2 (and master).
You can install the latest version with: pip install wildboar==1.1.2
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thanks
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Related Issues (20)
- tree.plot_tree(clf) for ShapeletDecisionTree class HOT 2
- __version__ missed HOT 1
- _joblib_parallel_args removed from scikit-learn HOT 3
- ShapeletForestEmbedding returns a matrix of all ones HOT 1
- RocketClassifier with n_jobs > 1 while using cross_validation does not work
- RocketClassifier predict_proba is not working
- RocketClassifier does not have a classes_-property
- 'IsolationShapeletForest' object has no attribute 'n_dims_'
- Bug when using dict or list scoring in importances
- Transform of SAX and PAA does not check if fitted
- ShapeletForestClassifier does not support single dimension 3D input (i.e. shape (10, 1, 20)) HOT 2
- Load multiple datasets with merge_train_test=False
- Support pairwise_distance(2d-array, 3d-array) HOT 2
- will it work for windows ? HOT 3
- Assigned leaf node in decision_path() HOT 2
- Unecessary splits in shapele trees
- CI builds fail on Windows.
- Raises ModuleNotFoundError when importing the datasets module
- Update What's New for Version 1.2
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