hummingbird.ml.containers._sklearn_api_containers¶
- class hummingbird.ml.containers._sklearn_api_containers.SklearnContainer(model, n_threads=None, batch_size=None, extra_config={})[source]¶
Bases:
ABC
- _abc_impl = <_abc_data object>¶
- _run(function, *inputs)[source]¶
This function scores the full dataset at once. See BatchContainer below for batched scoring.
- property model¶
- class hummingbird.ml.containers._sklearn_api_containers.SklearnContainerAnomalyDetection(model, n_threads, batch_size, extra_config={})[source]¶
Bases:
SklearnContainerRegression
Container mirroring Sklearn anomaly detection API.
- _abc_impl = <_abc_data object>¶
- abstract _decision_function(*inputs)[source]¶
This method contains container-specific implementation of decision_function.
- class hummingbird.ml.containers._sklearn_api_containers.SklearnContainerClassification(model, n_threads, batch_size, extra_config={})[source]¶
Bases:
SklearnContainerRegression
Container mirroring Sklearn classifiers API.
- _abc_impl = <_abc_data object>¶
- class hummingbird.ml.containers._sklearn_api_containers.SklearnContainerRegression(model, n_threads, batch_size, is_regression=True, is_anomaly_detection=False, extra_config={}, **kwargs)[source]¶
Bases:
SklearnContainer
Abstract container mirroring Sklearn regressors API.
- _abc_impl = <_abc_data object>¶
- abstract _predict(*input)[source]¶
This method contains container-specific implementation of predict.
- predict(*inputs)[source]¶
Utility functions used to emulate the behavior of the Sklearn API. On regression returns the predicted values. On classification tasks returns the predicted class labels for the input data. On anomaly detection (e.g. isolation forest) returns the predicted classes (-1 or 1).
- class hummingbird.ml.containers._sklearn_api_containers.SklearnContainerTransformer(model, n_threads=None, batch_size=None, extra_config={})[source]¶
Bases:
SklearnContainer
Abstract container mirroring Sklearn transformers API.
- _abc_impl = <_abc_data object>¶