Examples

Tricky issue when converting CountVectorizer or TfidfVectorizer

Tricky issue when converting CountVectorizer or TfidfVectorizer

Train and deploy a scikit-learn pipeline

Train and deploy a scikit-learn pipeline

Convert a pipeline with a LightGBM classifier

Convert a pipeline with a LightGBM classifier

Black list operators when converting

Black list operators when converting

What is the opset number?

What is the opset number?

Intermediate results and investigation

Intermediate results and investigation

Store arrays in one onnx graph

Store arrays in one onnx graph

Dealing with discrepancies (tf-idf)

Dealing with discrepancies (tf-idf)

Modify the ONNX graph

Modify the ONNX graph

Converter for WOE

Converter for WOE

Benchmark ONNX conversion

Benchmark ONNX conversion

Dataframe as an input

Dataframe as an input

One model, many possible conversions with options

One model, many possible conversions with options

Implement a new converter using other converters

Implement a new converter using other converters

Issues when switching to float

Issues when switching to float

Convert a pipeline with a LightGBM regressor

Convert a pipeline with a LightGBM regressor

Change the number of outputs by adding a parser

Change the number of outputs by adding a parser

Choose appropriate output of a classifier

Choose appropriate output of a classifier

Convert a pipeline with a XGBoost model

Convert a pipeline with a XGBoost model

A new converter with options

A new converter with options

Convert a pipeline with a CatBoost classifier

Convert a pipeline with a CatBoost classifier

Two ways to implement a converter

Two ways to implement a converter

Implement a new converter

Implement a new converter

Converter for pyod.models.iforest.IForest

Converter for pyod.models.iforest.IForest

Converter for WOEEncoder from categorical_encoder

Converter for WOEEncoder from categorical_encoder

Issues with FunctionTransformer

Issues with FunctionTransformer

TfIdf and sparse matrices

TfIdf and sparse matrices

FeatureHasher, pandas values and unexpected discrepancies

FeatureHasher, pandas values and unexpected discrepancies