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

1.10.4

• Use of sigmoid in SGDClassifier converter (#811)
• Reduce import time by 1 second (#801)
• Fix output shape for nearest neighbors regressor models (#799)
• Fix LinearRegressor converter (coef dimension) + fix bug with apply_clip (#795)

1.10.3

• Improve error message in ColumnTransformer parser (#792)
• Add logging in OneHotEncoder (#790)
• Fix converters for MinMaxScaler, GaussianProcessRegressor (Scan) (#791)

1.10.2

• Support non ascii characters in variable names (#784)
• Add option class_output_labels to expose class labels for a classifier (#776)
• Fix issue while converting graph with operator If (#781)
• Implements option zipmap for MultiOutputClassifier (#775)
• Modify tfidf_transformer to enable custom vocabulary and approximate sublinear-tf scaling without sparse containers (#777) (@adam444555)
• Enable RandomForestClassifier in converter for CalibrationClassifierCV (#772)

1.10.0

Features

• Add parameter naming to rename all intermediate results (#756)
• Add a function to update initializers in a ONNX model (#758)
• Support for scikit-learn==1.0 (#752)

Bug fixes

• Handle double with CalibratedClassifierCV (#753)
• Fix a bug with TfIdfConverter and pruned terms (#747)

Converters

• Replace Normalizer, Scaler, LinearRegressor, LinearClassifier by standard ONNX operators (#755)
• Add converters for TweedieRegressor, PoissonRegressor, QuantileRegressor (#750)
• Add converter for RandomTreesEmbedding (#751)

1.9.3

Bug fixes

• Fix LinearSVC, SVC in CalibratedClassifierCV (#742)
• Add function to store constant as initializer into the ONNX graph (#743)
• Fix missing types with two subestimators in a converter (#729)
• Fix conversion when a pipeline is one estimator in parameter estimators (Voting, ...) (#723)
• Fix converter for GridSearchCV (#722)
• Fixes #703, Interpet parameter value in ConstantOfShape (#709)
• Simplify onnx_parser API (#727)
• Refactoring, remove reversed name, simplify topology (#726)

Converters

• Add converter for LocalOutlierFactor (#741)
• Add converter for KernelPCA (#737)
• Add converters for MultiOutputRegressor and MultiOutputClassifier (#714),
  Use Sequence instead of Tensor for MultiOutputClassifier probabilities (#730),
  Remove option ZipMap for MultiOutputClassifier (#721)
• Add custom WOETransformer and its conversion to ONNX (#720)
• Support option score_samples with IsolationForest converter (#735)

1.9.2

• #697: support certain special characters in raw name
• #701: more verbosity for long models

1.9.1

• #689: Support onnx==1.9.0
• #694: Support missing string values with SimpleImputer
• #692: Fix Scaler converter, fix OnnxSubEstimator not directly connected to the converter inputs
• #691: Remove trivial Runtime error in SVM converter
• #682: fix type issue in AdaBoostClassifier (apply_clip)
• #680: Support conversion of StandardScaler with Double and norm L2
• #677: Add annotation to converters and shape calculator
• #676: Remove dependency on six

1.9.0

• Fix topological order after the model is converted #665, #667
• Enables opset 14 and enables onnxruntime 1.8.0 on CI, remove CI for onnxruntime<1.5.0 #664
• Add support for Int8, UInt8 #648
• Add option nan to CountVectorizer to avoid discrepencies with the use of sparse matrix #651
• Implements kernel cosine #641
• Removes class OnnxSubOperator, refactoring of class OnnxOperator #631

1.8.0

API

• Support for opset 13 #536
• Implements option zipmap='columns' to split output of a classifier into multiple vectors #550
• Support double for linear models, VotingRegressor #561
• Add option return_std to BayesianRidge converter #580
• Support attributes of type numpy.matrix #598
• Support types int8, uint8 as inputs #544
• Bagging converters support max_features, bootstrap_features #515

Fixes

• Fix issue with CalibratedClassifier 0.24 #556
• Fix bug in RadiusNeighborsClassifier, RadiusNeighborsRegressor #596
• Fix issue HistGradientBoosting 0.24 #525
• Fix OneVsRestClassifier converter for multilabel classification #568
• Fix function update_registered_converter for custom classifier #606

New converters

• GaussianProcessClassifier #579