Releases: onnx/sklearn-onnx
Releases · onnx/sklearn-onnx
1.18.0
- Add converter for TunedThresholdClassifierCV #1107
- Changes main opset in function to_onnx #1109
- Avoid concatenation if not needed #1110
- Update and Fix documentation #1113
- Support fill_value for SimpleImputer with string data #1123
- Remove unnecessary options for Regressor #1124
- OrdinalEncoder handle encoded_missing_value and unknown_value #1132
- Create output_onnx_single_probability.py #1139 #1141
1.17.0
- Upgrade the maximum supported opset to 21, update requirements to scikit-learn>=1.1, older versions are not tested anymore, #1098
- Support infrequent categories for OneHotEncoder #1029
- Support kernel Matern in Gaussian Process #978
- Fix for multidimensional gaussian process #1097
- Minor fixes to support scikit-learn==1.5.0 #1095
- Fix the conversion of pipeline including pipelines, issue #1069, #1072
- Fix unexpected type for intercept in PoissonRegressor and GammaRegressor #1070
- Add support for scikit-learn 1.4.0, #1058, fixes issues Many examples in the gallery are showing "broken", TFIDF vectorizer target_opset issue, Tfidfvectorizer with sublinear_tf fails, despite opset version set to greater than 11.
1.16.0
- Supports cosine distance (LocalOutlierFactor, ...) #1050,
- Supports multiple columns for OrdinalEncoder #1044 (by @max-509)
- Add an example on how to handle FunctionTransformer #1042, Versions of scikit-learn < 1.0 are not tested any more.
- Supports lists of strings as inputs for FeatureHasher #1036, #1036
- Fix OneHotEncoder when categories indices to drop are not None #1028
- fFx converter for AdaBoost estimators in scikit-learn==1.3.1 #1027
- Add function 'add_onnx_graph' to insert onnx graph coming from other converting,
libraries within the converter mapped to a custom estimator #1023, #1024 - Add option 'language' to converters of CountVectorizer, TfIdfVectorizer #1020
Contributors
max-509
Assets 2
1.15.0: Fix converter for DecisionTreeClassifier if n_classses == 1 (#1008)
1.14.1
1.14
- #968 Add an example to convert a pipeline with CatBoostClassifier
- #967 Update CI with onnxruntime==1.14.0 (with some code logic changed to to adapt ORT 1.14)
- #963 Fix use of split operator with opset 18
- #960 Avoid unnecessary loop iterations
- #959 Fix type issue when using FeatureVectorizer
- #957 Handle FeatureUnions with nested FeatureUnion or ColumnTransformers
- #953 Renames n_features_ into n_features_in_ for scikit-learn 1.2
- #952 Adding check for n_features in skl gb
- #947 Add converter for FeatureHasher
- #944 Update requirements and CI
- #943 Dedup in requirements
- #942 Fix a bug in identity removal (local variables)
- #941 Supppot log_loss in SDGClassifier converter (scikit-learn >= 1.1)
- #940 Add converter for WhiteKernel (gaussian processes)
- #938 Take raw_name from user inputs
- #935 Removes two warnings due to scipy update
- #934 Add CodeQL workflow
- #933 Fix issue #929, less Cast op in concat_op.py
- #931 Fix a broken example in the documentation
- #930 Added support for passthrough connection to stacking estimator
- #917 Fix option stop_words='english' in TfldVectorizer
- #916 Fixes documentation
1.13
new converters
- add OneVsOne classifier converter
- add QuadraticDiscriminantAnalysis converter
- add GammaRegressor
improvements
- improve unit test for linear classifier
- move code ovr_decision_function as a pseudo-operator
- shorten CI pipeline
- add Double/Int64 data type for GammaRegressor unittest
- support arrays for length_scale in kernel RBF
- better error messages for TfidfVectorizer
- Implements TraceableCountVecrotizer and TraceableTfidfVectorizer
bug fix
- bug fix for multiple-output not correct in Random Forest