v1.5.0

skl2onnx version 1.5.0 is now available! This version features ONNX Opset 10 support, increased test and operator coverage, improved documentation, and a new way to write converters.

How do I install the latest skl2onnx package?

pip install skl2onnx --upgrade

Highlights since the last release

• Update package version and onnxconverter-common dependency to 1.5.0 (#177)
• New way to write converters based on OnnxOperators (#128)
• Clean OnnxOperator before converting into ONNX (#149)
• Increase operator coverage for SciKitLearn
  • Fixed multi-class LR with intercept set to None (#135)
  • Fixes #113, convert OneVsRestClassifier multilabel (#142)
  • Supports passthrough and remainder='passthrough' for ColumnTransformer converter (#152)
  • Support int features in linear and non-linear regressor converter(s) (#154, #157)
  • Fixes #147, fix probabilities when multi_class == 'multinomial' (#150)
• ONNX Opset 10 updates
  • Fixed slice op to align with opset 10 changes (#116)
  • Update CountVectorizer and TfidfVectorizer (#111)
  • Updated TopK node to align with changes in opset 10 (#91)
• Extend documentation, clarify error messages
  • Follow Pep8 conventions (#141, #143, #144, #145)
  • Better exceptions, better error message, extend documentation (#146)
• Increase test coverage
  • Added SGDClassifier converter unit tests (#138)
  • Handle scikit-learn dev version when using StrictVersion in tests (#139)
  • Added unit tests to increase coverage (#140, #170)
  • Add unit tests for investigate.py (#161)
  • Fix issues raised by scikit-learn 0.22. (#175)