Releases: autogluon/fev
v0.6.1
v0.6.0
🚨 Major Breaking Changes
The new 0.6.0 release contains lots of improvements and breaking changes to the API. For existing users, we recommend taking a look at the updated tutorials to get familiar with the changes and the new functionality.
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Task API Redesign:
Tasknow contains multiple rolling windows,TaskGeneratorclass is deprecated.New code for evaluation on multiple rolling windows:
task = fev.Task(..., num_windows=2) predictions_per_window = [] for window in task.iter_windows(): past_data, future_data = window.get_input_data() predictions_per_window.append(model.predict(past_data, future_data)) # A single summary with average score across evaluation windows summary = task.evaluation_summary(predictions_per_window, model_name="my_model")
Old code (version <=0.5.0)
task_generator = fev.TaskGenerator(..., num_rolling_windows=2) for task in task_generator.generate_tasks(): past_data, future_data = task.get_input_data() predictions = model.predict(past_data, future_data) # One summary per evaluation window summary = task.evaluation_summary(predictions, model_name="my_model")
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Renamed parameters: Deprecated
Task/TaskGeneratorparameter names:num_rolling_windows→num_windowsrolling_step_size→window_step_sizecutoff→initial_cutofftarget_column→targetmultiple_target_columns→generate_univariate_targets_fromlead_time→ ignoredexcluded_column_names→ ignored
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Covariate specification: Names of covariate columns now need to provided explicitly during
Taskcreation usingknown_dynamic_columns,past_dynamic_columns,static_columnskeyword arguments. Columns present in the dataset -
Leaderboard changes:
fev.leaderboard()now usesskill_scoreandwin_rateinstead ofgmean_rel_errorandavg_rank. The method also optionally returns 95% confidence intervals based on bootstrap. -
Updated results and benchmark definitions on GitHub: Benchmark task definitions, results, and model wrappers on the
mainbranch have been updated to be compatible withv0.6.0. Please view the old branches (e.g.,v0.5.0) to access the old task definitions, results and model wrappers.
What's Changed
- Add multivariate <-> univariate conversion support by @shchur in #27
- Refactor
Taskclass to include multiple rolling window evaluations by @shchur in #33 - Make metrics customizable by @canerturkmen in #35
- Update model wrappers and results to be compatible with the new
Taskdesign - Update README.md by @shchur in #26
- Speed up
fev.utils.validate_time_series_datasetby @shchur in #29 - Implement
DartsAdapterby @shchur in #30 - Use ordinal encoding for dynamic categorical features in GluonTSAdapter by @shchur in #31
- Make covariate column names explicit by @shchur in #34
- Minor fixes to
Taskby @shchur in #37 - Fix Task.to_dict() with dict-based metrics by @shchur in #38
- Refactor analysis code by @shchur in #36
- Add results for TimeCopilot by @AzulGarza in #39
- Add static webpages with documentation using
mkdocsby @shchur in #42 - Update results to v0.6.0 by @shchur in #43
- Update model wrappers for v0.6.0 by @shchur in #44
- Update readme for v0.6.0 by @shchur in #45
New Contributors
- @canerturkmen made their first contribution in #35
- @AzulGarza made their first contribution in #39
Full Changelog: v0.5.0...v0.6.0
v0.6.0rc4
This is a pre-release version.
What's Changed
- Refactor analysis code by @shchur in #36
- Add static webpages with documentation using
mkdocsby @shchur in #42 - Update results to v0.6.0 by @shchur in #43
- Update model wrappers for v0.6.0 by @shchur in #44
- Update readme for v0.6.0 by @shchur in #45
Full Changelog: v0.6.0rc3...v0.6.0rc4
v0.6.0rc3
This is a pre-release version.
What's Changed
- Use ordinal encoding for dynamic categorical features in GluonTSAdapter by @shchur in #31
- Refactor
Taskclass to include multiple rolling window evaluations by @shchur in #33 - Make covariate column names explicit by @shchur in #34
- make metrics customizable by @canerturkmen in #35
- Minor fixes to
Taskby @shchur in #37 - Fix Task.to_dict() with dict-based metrics by @shchur in #38
New Contributors
- @canerturkmen made their first contribution in #35
Full Changelog: v0.6.0rc2...v0.6.0rc3
v0.6.0rc2
v0.6.0rc1
v0.5.0
Highlights
- Multivariate forecasting support: The users can now create multivariate tasks by setting the
target_columnto alist[str]with names of target columns when creating aTask. Check out the updated tutorial for more details. - API changes: The following
Taskattributes have been deprecated. Results containing old names can still be used, but creating new tasks with deprecated attributes will produce a warning.multiple_target_columnshas been renamed togenerate_univariate_targets_from.min_ts_lengthhas been replaced bymin_context_length.
- Improved handling of short series: Previously, if some time series in the dataset were too short for the chosen
horizonandcutoffcombination, and exception would be raised. Now, these series will be automatically filtered out during dataset loading.
Changelog
- Add support for multivariate forecasting in
Taskby @shchur in #15 - Improve time series filtering based on
cutoff,horizonandmin_context_lengthby @shchur in #18 - Add TiRex results by @apointa in #17
- Fix seasonal differences for short series by @shchur in #20
- Expose prediction validation as a public method by @abdulfatir in #21
- Handle
DatasetDictinclean_and_validate_predictionsby @abdulfatir in #22
New Contributors
- @apointa made their first contribution in #17
- @abdulfatir made their first contribution in #21
Full Changelog: v0.4.1...v0.5.0