SparkMLPredictor: Performs predictions against an MLeap serialized SparkML...

In DyfanJones/sagemaker-r-mlframework: sagemaker machine learning developed by amazon

Performs predictions against an MLeap serialized SparkML model.

Description

The implementation of :meth:'~sagemaker.predictor.Predictor.predict' in this 'Predictor' requires a json as input. The input should follow the json format as documented. “predict()“ returns a csv output, comma separated if the output is a list.

Super classes

sagemaker.mlcore::PredictorBase -> sagemaker.mlcore::Predictor -> SparkMLPredictor

Methods

Public methods

• SparkMLPredictor$new()

• SparkMLPredictor$clone()

Inherited methods

• sagemaker.mlcore::Predictor$delete_endpoint()

• sagemaker.mlcore::Predictor$delete_model()

• sagemaker.mlcore::Predictor$delete_predictor()

• sagemaker.mlcore::Predictor$disable_data_capture()

• sagemaker.mlcore::Predictor$enable_data_capture()

• sagemaker.mlcore::Predictor$endpoint_context()

• sagemaker.mlcore::Predictor$format()

• sagemaker.mlcore::Predictor$list_monitors()

• sagemaker.mlcore::Predictor$predict()

• sagemaker.mlcore::Predictor$update_data_capture_config()

• sagemaker.mlcore::Predictor$update_endpoint()

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Method new()

Initializes a SparkMLPredictor which should be used with SparkMLModel to perform predictions against SparkML models serialized via MLeap. The response is returned in text/csv format which is the default response format for SparkML Serving container.

Usage

SparkMLPredictor$new(
  endpoint_name,
  sagemaker_session = NULL,
  serializer = CSVSerializer$new(),
  ...
)

Arguments

endpoint_name

(str): The name of the endpoint to perform inference on.

sagemaker_session

(sagemaker.session.Session): Session object which manages interactions with Amazon SageMaker APIs and any other AWS services needed. If not specified, the estimator creates one using the default AWS configuration chain.

serializer

(sagemaker.serializers.BaseSerializer): Optional. Default serializes input data to text/csv.

...

: Additional parameters passed to the :class:'~sagemaker.Predictor' constructor.

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Method clone()

The objects of this class are cloneable with this method.

Usage

SparkMLPredictor$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-mlframework documentation built on March 18, 2022, 7:41 a.m.