📚 This is the first Tribuo point release after the initial public announcement. It fixes many of the issues our early users have found, and improves the documentation in the areas flagged by those users. We also added a couple of small new methods as part of fixing the bugs, and added two new tutorials: one on columnar data loading and one on external model loading (i.e. XGBoost and ONNX models).
🐛 Bugs fixed:
- 🛠 Fixed a locale issue in the evaluation tests.
- 🛠 Fixed issues with RowProcessor (expand regexes not being called, improper provenance capture).
FileNotFoundExceptionrather than a mysterious
NullPointerExceptionwhen it can't find the file.
- 🛠 Fixed issues in
JsonDataSource(consistent exceptions thrown, proper termination of reading in several cases).
- 🛠 Fixed an issue where regression models couldn't be serialized due to a non-serializable lambda.
- 🛠 Fixed UTF-8 BOM issues in CSV loading.
- 🛠 Fixed an issue where
LibSVMTrainerdidn't track state between repeated calls to train.
- 🛠 Fixed issues in the evaluators to ensure consistent exception throwing when discovering unlabelled or unknown ground truth outputs.
- 🛠 Fixed a bug in ONNX
LabelTransformerwhere it wouldn't read pytorch outputs properly.
- ⬆️ Bumped to OLCUT 5.1.5 to fix a provenance -> configuration conversion issue.
🆕 New additions:
- ➕ Added a method which converts a Jackson
Mapsuitable for the
- ➕ Added missing serialization tests to all the models.
- ➕ Added a getInnerModels method to
XGBoostModelto allow users to access a copy of the internal models.
- 📚 More documentation.
- Columnar data loading tutorial.
- External model (XGBoost & ONNX) tutorial.
⚡️ Dependency updates:
- OLCUT 5.1.5 (brings in jline 3.16.0 and jackson 2.11.3).
🚀 This is the first public release of the Tribuo Java Machine Learning library. Tribuo provides classification, regression, clustering and anomaly detection algorithms along with data loading, transformation and model evaluation code. Tribuo also provides support for loading external ONNX models and scoring them in Java as well as support for training and evaluating deep learning models using TensorFlow.
Tribuo's development started in 2016 led by Oracle Labs' Machine Learning Research Group, and has been in production inside Oracle since 2017. It's now available under an Apache 2.0 license, and we'll continue to develop it in the open, including accepting community PRs under the Oracle Contributor Agreement.