Framework and bug fixes:
- #229: improves LabelBinarizer
- #327: add option to remove ZipMap operator
- #382: fix final opset in topology
- #445: add missing cast when using operator concat
- #447: add parameters to rename ONNX outputs
- #451: add white list, black list of operators, the converters can use this information to change the way a model is converted into ONNX
- #464: fix issues in ArrayFeatureExtractor, OneHotEncoder
- #466: BaggingClassifier supports zipmap options
- #473, #460, #458, #426, #422: sklearn-onnx works with onnx development version, works with opset 12, scikit-learn 0.23
New converters:
- #318: PLSRegression
- #341: HistGradientBoostingRegressor
- #315, #344, #345, #347, #348, #349, #356, #421: multi-label support
- #358: HistGradientBoostingClassifier
- #362, #363, #364, #366, #369, #371: support decision function
- #377: CalibratedClassifierCV
- #375: CategoricalNB
- #381, #382: StackingClassifier
- #395: KNeighborsTransformer
- #384: StackingRegressor
- #403: PowerTransformer
- #404, #469: KNNImputer
- #419: support more kernels in SVM
- #431: GaussianMixture
- #438: GaussianRandomProjection
- #450: handle OVR decision function (SVM)