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

1.15.0: Fix converter for DecisionTreeClassifier if n_classses == 1 (#1008)

• Add new matrix for ORT 1.15 testing #992
• Update to sklearn==1.3.0 #1002
• Improves robustness in node ordering #1004
• Fix converter for DecisionTreeClassifier in n_classed==1 #1008
• [Internal] Refactor with black #1009

1.14.1

what's improved:

• #988 Adapting onnx 1.14 release
• #971 Use Furo Theme (doc)
• #972 Update doc to version 1.14.0
• #979 Implement converter for _ConstantPredictor
• #983 Remove unnecessary files
• #986 Swayand/bug fix min max scaler with clip

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

issues closed

• #796
• #797
• #807
• #872
• #874
• #882
• #901
• #912

skl2onnx 1.12

• Add new Gamma Regressor converter #894
• Update max supported opset, update CI to python 3.10 #892
• Add example about TfldVectorizer
• Improve some other examples and remove unnecessary examples
• Fix documents link missing bug
• Fix some GitHub issues

1.11.2

• LocalOutlierFactor n_neighbors bugfix #821
• MAINT compat link function and loss for sklearn 1.1 #863
• add sgd_oneclass svm converter #860

1.11.1

• Fix WOE converter to adapt OnnxRuntime implementation (#849)
• Refine few documents

1.11

• Fix potential bug in IsolationForest and WOETransformer converter due to latest onnx update #835
• LocalOutlierFactor n_neighbors bugfix #836
• Fix converter for SimpleImputer when strategy='MostFrequent' and full_value is None #834
• Enable Double input type for RandomForest and ZipMap #826
• Allow empty array as feature_names_out #832
• Fixes for onnx==1.11.0 #824
• Fix unit test with unfitted models, fix PLSRegression 1.1 #827
• Fix a validation verifying dimension type #823
• Fixes issue #817 and method _propagation_status #820
• Fixes #813, support unsigned class labels in MLPClassifier #818
• Fixes #814, fix conversion of TreeEnsemble due to a change of the loss name in scikit-learn #819