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Release v0.4.0 #267
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Release v0.4.0 #267
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Contributor
mloning
commented
May 29, 2020
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edited
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edited
- fix readme
New contributions guidelines
Fixes RISE in example notebook
updating ESTIMATOR_OVERVIEW.md with full taxonomy
* Adds ROCKET (transform only) to transformers. * Update proposed ROCKET implementation and add unit test. Updates: absolute imports, remove fit_transform(...), update constructor, fit(...) and transform(...), update internal implementation, add random seed argument to constructor, move _to_numpy(...) / dataframe_to_numpy(...) to utils/data_container.py, add basic test in transformers/tests/test_Rocket.py. * Added some `np.testing.assert...` checks. * Add numba to `requirements.txt`. * Add numba to dependencies. * Increase pandas min version to 0.24 for `.to_numpy()` for `dataframe_to_numpy(...)` in `utils/data_container.py'. * Terminology change: `num_examples` to `n_instances', `num_channels` to `n_columns`, `input_length` to `n_timepoints`. * Update validation import; add default value for num_kernels parameter; add example notebook. * Update estimator overview. * Updates as requested. Co-authored-by: Markus Löning <markus.loning.17@ucl.ac.uk>
* add mrseql classifier * fix windows installation, remove files,add input checking * small fix * fix method to check multiclass * add oneversusall class * add mrseql unit test * Fix unit test * edit ESTIMATOR * format code, add docstring, edit notebook example * minor clean
* finished input checks * tsfresh feature extraction (univariate and multivariate * refactored summarise and included convert_data in utils * added tests for transformer, performed validation checks * changed example * added feature selector and example notebook * Added validation checks, removed dependencies * clean up * Delete forecasting.ipynb * restored forecasting notebook * added tsfresh as soft dependency for tests * added tsfresh as soft dependency for tests * added tsfresh as soft dependency for tests * removed efficient settings * added docstrings, fixed typo * improved setting of defaults, minor udpates * updated docstrings * added code comments * Update ESTIMATOR_OVERVIEW.md Co-authored-by: Ayushmaan <ayushmaanseth@gmail.com>
* Update documentation of TimeSeriesForestClassifier. Co-authored-by: Markus Löning <markus.loning.17@ucl.ac.uk>
* updated setup.py * updated binder * added support for python=3.8 * added support for manylinux wheels * added CI on azure DevOps * added automated release script * added automatic PyPI upload from CI services * added flake8 linting
* forecasting grid-search CV * temporal cross-validation * Theta forecaster * Naive forecasters * SES forecasters * sMAPE and MASE loss * reduction meta-forecasters * detrender * TransformedTargetForecaster, * AutoARIMA * deseasonaliser * fitted param extractor * PolynomialTrendForecaster * ensemble and stacking forecaster * sklearn transformer adaptor to single series setting * boxcox transformer with bounds on lambda Co-authored-by: big-o <big-o@users.noreply.github.com>
* folder reorganisation * unit testing for basic API for all estimators * consistent input checks * refactored high-level into benchmarking * renamed n_trees to n_estimators * refactored transformer module * enforce PEP8 linting with flake8 * fixed warnings * updated sklearn version Co-authored-by: Patrick Rockenschaub <patrick.rockenschaub.15@ucl.ac.uk> Co-authored-by: Matthew Middlehurst <pfm15hbu@uea.ac.uk> Co-authored-by: Thach Le Nguyen <lenguyenthach141@gmail.com> Co-authored-by: angus924 <55837131+angus924@users.noreply.github.com>
* added all-contributors specs * added new issue template for doc improvements * updated estimator overview and contributing guidelines * updated website * updated changelog * added about page * added mission statement * added new logo
* refactored TimeSeriesForestRegressor and TimeSeriesForestClassifier Co-authored-by: mloning <markus.loning.17@ucl.ac.uk>
* added release drafter workflow
* add feature importance graph to TSF Co-authored-by: Markus Löning <markus.loning@gmail.com>
* added release drafter workflow
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