New Features
- add dummy estimator for seasonal_naive (#1598)
- Add STL-AR as one more R baseline model (#1568)
- Allow validation data for TabularEstimator. (#1562)
- QRX fixes and added functionality (#1544)
- Extend FileDataset's Parameters to load_datasets (#1538)
- Serde: Allow encoding of functions and methods. (#1519)
- Settings: Enable partial assignment (#1504)
- Settings: Support for nested args in _inject. (#1503)
Transform.apply
(#1494)- PyTorch implementation of DeepAR (#1460)
- support Min freq for get_seasonality() method (#1459)
- add deep renewal processes for intermittent demand forecasting (#1458)
- Add transform objects for dealing with sparse time series. (#1421)
- spliced binned pareto (#1410)
- Add callbacks mechanism to Trainer class (#1168)
Bug Fixes
- Fix frequency metadata bug for lstnet datasets (#1593)
- Fix single dispatch register for py36 (#1591)
- R fixes for methods that produce point forecasts or prediction intervals directly (#1564)
- Fix computation of OWA (#1557)
- Fixed QRX bug: ".values()" to ".values" (#1552)
- QRX fixes and added functionality (#1544)
- Fix serde issue with some distribution output types, add test (#1543)
- Add item_id to r forecast predictors (#1537)
- fix ProphetPredictor serialization issue (#1535)
- Add constant dummy time features to TFT for yearly data (#1518)
- Settings: Fix partial assignment. (#1516)
- Fix anomaly detection example (#1515)
- Fix Settings._inject to check if it can provide the value. (#1501)
- Change miniver fallback version from
unknown
to0.0.0
. (#1457) - Fix get_lags_for_frequency for minute data in DeepVAR (#1455)
- Fix missing import in gluonts.mx.model.GluonEstimator (#1450)
- Fix train-test split data leakage for m4_yearly and wiki-rolling_nips. (#1445)
- fix compatibility for pandas < 1.1 in
time_feature/_base.py
(#1437) - fix edge case in iteration based model averaging (#1345)
Breaking Changes
Other Changes & Improvements
- shallow import for
gluonts.mx
module (#1592) - Mark torch distribution inference tests as flaky (#1586)
- Update REFERENCES.md (#1583)
- Delete pytorch_predictor_example.ipynb (#1574)
- Improve tests for R methods (#1567)
- Rename flake8 action step. (#1555)
- Set max_idle_transforms to the length of the dataset (#1546)
- Add datasets from forecastingdata.org (#1542)
- Train invoke with (#1530)
- Consolidate ZeroFeature from DeepState (#1522)
- Fix indentation (#1500)
- Simplify
loader.py
(#1495) - adjustments to variable length functionality in batchify (#1442)
- Use miniver for version resolution. (#1434)
- Add docstrings for metrics. (#1422)
- Fixes for MXNet 1.8 (#1403)