interpret_community.common.model_wrapper module¶

Defines helpful model wrapper and utils for implicitly rewrapping the model to conform to explainer contracts.

class interpret_community.common.model_wrapper.WrappedClassificationModel(model, eval_function)¶

A class for wrapping a classification model.

predict(dataset)¶

Predict the output using the wrapped classification model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict on.

predict_proba(dataset)¶

Predict the output probability using the wrapped model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict_proba on.

class interpret_community.common.model_wrapper.WrappedClassificationWithoutProbaModel(model)¶

A class for wrapping a classifier without a predict_proba method.

Note: the classifier may not output numeric values for its predictions. We generate a trival boolean version of predict_proba

predict(dataset)¶

Predict the output using the wrapped regression model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict on.

predict_proba(dataset)¶

Predict the output probability using the wrapped model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict_proba on.

class interpret_community.common.model_wrapper.WrappedPytorchModel(model)¶

A class for wrapping a PyTorch model in the scikit-learn specification.

predict(dataset)¶

Predict the output using the wrapped PyTorch model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict on.

predict_classes(dataset)¶

Predict the class using the wrapped PyTorch model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict on.

predict_proba(dataset)¶

Predict the output probability using the wrapped PyTorch model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict_proba on.

class interpret_community.common.model_wrapper.WrappedRegressionModel(model, eval_function)¶

A class for wrapping a regression model.

predict(dataset)¶

Predict the output using the wrapped regression model.

Parameters:	dataset (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The dataset to predict on.

interpret_community.common.model_wrapper.wrap_model(model, examples, model_task)¶

If needed, wraps the model in a common API based on model task and prediction function contract.

Parameters:	model (model with a predict or predict_proba function.) – The model to evaluate on the examples. examples (interpret_community.dataset.dataset_wrapper.DatasetWrapper) – The model evaluation examples. model_task (str) – Optional parameter to specify whether the model is a classification or regression model. In most cases, the type of the model can be inferred based on the shape of the output, where a classifier has a predict_proba method and outputs a 2 dimensional array, while a regressor has a predict method and outputs a 1 dimensional array.
Returns:	The wrapper model.
Return type:	model