Amazon Machine Learning
Definition of the public APIs exposed by Amazon Machine Learning
machinelearning(config = list())
config |
Optional configuration of credentials, endpoint, and/or region. |
svc <- machinelearning(
config = list(
credentials = list(
creds = list(
access_key_id = "string",
secret_access_key = "string",
session_token = "string"
),
profile = "string"
),
endpoint = "string",
region = "string"
)
)| add_tags | Adds one or more tags to an object, up to a limit of 10 |
| create_batch_prediction | Generates predictions for a group of observations |
| create_data_source_from_rds | Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS) |
| create_data_source_from_redshift | Creates a DataSource from a database hosted on an Amazon Redshift cluster |
| create_data_source_from_s3 | Creates a DataSource object |
| create_evaluation | Creates a new Evaluation of an MLModel |
| create_ml_model | Creates a new MLModel using the DataSource and the recipe as information sources |
| create_realtime_endpoint | Creates a real-time endpoint for the MLModel |
| delete_batch_prediction | Assigns the DELETED status to a BatchPrediction, rendering it unusable |
| delete_data_source | Assigns the DELETED status to a DataSource, rendering it unusable |
| delete_evaluation | Assigns the DELETED status to an Evaluation, rendering it unusable |
| delete_ml_model | Assigns the DELETED status to an MLModel, rendering it unusable |
| delete_realtime_endpoint | Deletes a real time endpoint of an MLModel |
| delete_tags | Deletes the specified tags associated with an ML object |
| describe_batch_predictions | Returns a list of BatchPrediction operations that match the search criteria in the request |
| describe_data_sources | Returns a list of DataSource that match the search criteria in the request |
| describe_evaluations | Returns a list of DescribeEvaluations that match the search criteria in the request |
| describe_ml_models | Returns a list of MLModel that match the search criteria in the request |
| describe_tags | Describes one or more of the tags for your Amazon ML object |
| get_batch_prediction | Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request |
| get_data_source | Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource |
| get_evaluation | Returns an Evaluation that includes metadata as well as the current status of the Evaluation |
| get_ml_model | Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel |
| predict | Generates a prediction for the observation using the specified ML Model |
| update_batch_prediction | Updates the BatchPredictionName of a BatchPrediction |
| update_data_source | Updates the DataSourceName of a DataSource |
| update_evaluation | Updates the EvaluationName of an Evaluation |
| update_ml_model | Updates the MLModelName and the ScoreThreshold of an MLModel |
## Not run: svc <- machinelearning() svc$add_tags( Foo = 123 ) ## End(Not run)
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