* Small docstring change for clarity
* Added tentative changes to docs
* Update website/docs/Use-Cases/Task-Oriented-AutoML.md
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Update flaml/model.py
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Updated model.py to reflect `n_jobs = None` suggestion
* Updated tutorial to reflect `n_jobs=None` suggestion
* Update model.py
Improved string
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* categorical choice can be ordered or unordered
* ordered -> order
* move choice into utils
* version comparison
* packaging -> setuptools
* import version
* version_parse
* test order for choice
* time series forecasting with panel datasets
- integrate Temporal Fusion Transformer as a learner based on pytorchforecasting
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py and test_forecast.py
- remove blank lines
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py to prevent errors
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py and data.py
- change forecast task name
- update documentation for fit() method
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
- add performance test
- use 'fit_kwargs_by_estimator'
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* add time index function
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py performance test
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update data.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update data.py to prevent type error
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update setup.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update for pytorch forecasting tft on panel datasets
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* - rename estimator
- add 'gpu_per_trial' for tft estimator
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update test_forecast.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* include ts panel forecasting as an example
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl_time_series_forecast.ipynb
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update documentations
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* "weights_summary" argument deprecated and removed for pl.Trainer()
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py tft estimator prediction method
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update model.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update `fit_kwargs` documentation
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* update automl.py
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* support latest xgboost version
* Update test_classification.py
* Update
Exists problems when installing xgb1.6.1 in py3.6
* cleanup
* xgboost version
* remove time_budget_s in test
* remove redundancy
* stop support of python 3.6
Co-authored-by: zsk <shaokunzhang529@gmail.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* init value type match
* bump version to 1.0.6
* add a note about flaml version in notebook
* add note about mismatched ITER_HP
* catch SSLError when accessing OpenML data
* catch errors in autovw test
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
* refactoring TransformersEstimator to support default and custom_hp
* handling starting_points not in search space
* addressing starting point more than max_iter
* fixing upper < lower bug
* update model.py
- change upper bound for "lags" hyperparameter
* update test_forecast.py
- add a test for a large dataset
* update sample.py
- pre-commit changes
* changed signature of automl.predict and automl.predict_proba to X
* XGBoostEstimator
* changed signature of Prophet predict to X
* changed signature of ARIMA predict to X
* changed signature of TS_SKLearn_Regressor predict to X
* add sklearn regressors as learners for ts_forecast task
* add direct forecasting strategy
warnings and errors for duplicate rows and missing values
- add preprocess for sklearn time series forecast
update automl.py
update test/test_forecast.py
* update model.py and test_forecast.py for cv eval_method
* add "hcrystalball" dependency in setup.py
* update automl.py
- add _validate_ts_data function for abstraction
- include xgb_limitdepth as a learner
* update model.py
- update search space for sklearn ts regressors
* update automl.py and test_forecast.py for numpy array inputs
* add documentations to model.py
* add documentation for removing catboost regressor
* update automl.py
- _validate_ts_data() function
Signed-off-by: Kevin Chen <chenkevin.8787@gmail.com>
* query logged runs
* mlflow log when using ray
* key check for newer version of ray #363
* catch importerror
* log and load AutoML model
* retrain if necessary when ensemble fails
