@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class GetEventPredictionRequest extends AmazonWebServiceRequest implements Serializable, Cloneable
NOOP| Constructor and Description |
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GetEventPredictionRequest() |
| Modifier and Type | Method and Description |
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GetEventPredictionRequest |
addEventVariablesEntry(String key,
String value)
Add a single EventVariables entry
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GetEventPredictionRequest |
addExternalModelEndpointDataBlobsEntry(String key,
ModelEndpointDataBlob value)
Add a single ExternalModelEndpointDataBlobs entry
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GetEventPredictionRequest |
clearEventVariablesEntries()
Removes all the entries added into EventVariables.
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GetEventPredictionRequest |
clearExternalModelEndpointDataBlobsEntries()
Removes all the entries added into ExternalModelEndpointDataBlobs.
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GetEventPredictionRequest |
clone()
Creates a shallow clone of this object for all fields except the handler context.
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boolean |
equals(Object obj) |
String |
getDetectorId()
The detector ID.
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String |
getDetectorVersionId()
The detector version ID.
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List<Entity> |
getEntities()
The entity type (associated with the detector's event type) and specific entity ID representing who performed the
event.
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String |
getEventId()
The unique ID used to identify the event.
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String |
getEventTimestamp()
Timestamp that defines when the event under evaluation occurred.
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String |
getEventTypeName()
The event type associated with the detector specified for the prediction.
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Map<String,String> |
getEventVariables()
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their
corresponding values for the event you are sending for evaluation.
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Map<String,ModelEndpointDataBlob> |
getExternalModelEndpointDataBlobs()
The Amazon SageMaker model endpoint input data blobs.
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int |
hashCode() |
void |
setDetectorId(String detectorId)
The detector ID.
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void |
setDetectorVersionId(String detectorVersionId)
The detector version ID.
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void |
setEntities(Collection<Entity> entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the
event.
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void |
setEventId(String eventId)
The unique ID used to identify the event.
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void |
setEventTimestamp(String eventTimestamp)
Timestamp that defines when the event under evaluation occurred.
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void |
setEventTypeName(String eventTypeName)
The event type associated with the detector specified for the prediction.
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void |
setEventVariables(Map<String,String> eventVariables)
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their
corresponding values for the event you are sending for evaluation.
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void |
setExternalModelEndpointDataBlobs(Map<String,ModelEndpointDataBlob> externalModelEndpointDataBlobs)
The Amazon SageMaker model endpoint input data blobs.
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String |
toString()
Returns a string representation of this object.
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GetEventPredictionRequest |
withDetectorId(String detectorId)
The detector ID.
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GetEventPredictionRequest |
withDetectorVersionId(String detectorVersionId)
The detector version ID.
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GetEventPredictionRequest |
withEntities(Collection<Entity> entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the
event.
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GetEventPredictionRequest |
withEntities(Entity... entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the
event.
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GetEventPredictionRequest |
withEventId(String eventId)
The unique ID used to identify the event.
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GetEventPredictionRequest |
withEventTimestamp(String eventTimestamp)
Timestamp that defines when the event under evaluation occurred.
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GetEventPredictionRequest |
withEventTypeName(String eventTypeName)
The event type associated with the detector specified for the prediction.
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GetEventPredictionRequest |
withEventVariables(Map<String,String> eventVariables)
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their
corresponding values for the event you are sending for evaluation.
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GetEventPredictionRequest |
withExternalModelEndpointDataBlobs(Map<String,ModelEndpointDataBlob> externalModelEndpointDataBlobs)
The Amazon SageMaker model endpoint input data blobs.
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addHandlerContext, getCloneRoot, getCloneSource, getCustomQueryParameters, getCustomRequestHeaders, getGeneralProgressListener, getHandlerContext, getReadLimit, getRequestClientOptions, getRequestCredentials, getRequestCredentialsProvider, getRequestMetricCollector, getSdkClientExecutionTimeout, getSdkRequestTimeout, putCustomQueryParameter, putCustomRequestHeader, setGeneralProgressListener, setRequestCredentials, setRequestCredentialsProvider, setRequestMetricCollector, setSdkClientExecutionTimeout, setSdkRequestTimeout, withGeneralProgressListener, withRequestCredentialsProvider, withRequestMetricCollector, withSdkClientExecutionTimeout, withSdkRequestTimeoutpublic void setDetectorId(String detectorId)
The detector ID.
detectorId - The detector ID.public String getDetectorId()
The detector ID.
public GetEventPredictionRequest withDetectorId(String detectorId)
The detector ID.
detectorId - The detector ID.public void setDetectorVersionId(String detectorVersionId)
The detector version ID.
detectorVersionId - The detector version ID.public String getDetectorVersionId()
The detector version ID.
public GetEventPredictionRequest withDetectorVersionId(String detectorVersionId)
The detector version ID.
detectorVersionId - The detector version ID.public void setEventId(String eventId)
The unique ID used to identify the event.
eventId - The unique ID used to identify the event.public String getEventId()
The unique ID used to identify the event.
public GetEventPredictionRequest withEventId(String eventId)
The unique ID used to identify the event.
eventId - The unique ID used to identify the event.public void setEventTypeName(String eventTypeName)
The event type associated with the detector specified for the prediction.
eventTypeName - The event type associated with the detector specified for the prediction.public String getEventTypeName()
The event type associated with the detector specified for the prediction.
public GetEventPredictionRequest withEventTypeName(String eventTypeName)
The event type associated with the detector specified for the prediction.
eventTypeName - The event type associated with the detector specified for the prediction.public List<Entity> getEntities()
The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."
public void setEntities(Collection<Entity> entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."
entities - The entity type (associated with the detector's event type) and specific entity ID representing who
performed the event. If an entity id is not available, use "UNKNOWN."public GetEventPredictionRequest withEntities(Entity... entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."
NOTE: This method appends the values to the existing list (if any). Use
setEntities(java.util.Collection) or withEntities(java.util.Collection) if you want to override
the existing values.
entities - The entity type (associated with the detector's event type) and specific entity ID representing who
performed the event. If an entity id is not available, use "UNKNOWN."public GetEventPredictionRequest withEntities(Collection<Entity> entities)
The entity type (associated with the detector's event type) and specific entity ID representing who performed the event. If an entity id is not available, use "UNKNOWN."
entities - The entity type (associated with the detector's event type) and specific entity ID representing who
performed the event. If an entity id is not available, use "UNKNOWN."public void setEventTimestamp(String eventTimestamp)
Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO 8601 standard in UTC.
eventTimestamp - Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO
8601 standard in UTC.public String getEventTimestamp()
Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO 8601 standard in UTC.
public GetEventPredictionRequest withEventTimestamp(String eventTimestamp)
Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO 8601 standard in UTC.
eventTimestamp - Timestamp that defines when the event under evaluation occurred. The timestamp must be specified using ISO
8601 standard in UTC.public Map<String,String> getEventVariables()
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their corresponding values for the event you are sending for evaluation.
You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
public void setEventVariables(Map<String,String> eventVariables)
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their corresponding values for the event you are sending for evaluation.
You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
eventVariables - Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and
their corresponding values for the event you are sending for evaluation. You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
public GetEventPredictionRequest withEventVariables(Map<String,String> eventVariables)
Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and their corresponding values for the event you are sending for evaluation.
You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
eventVariables - Names of the event type's variables you defined in Amazon Fraud Detector to represent data elements and
their corresponding values for the event you are sending for evaluation. You must provide at least one eventVariable
To ensure most accurate fraud prediction and to simplify your data preparation, Amazon Fraud Detector will replace all missing variables or values as follows:
For Amazon Fraud Detector trained models:
If a null value is provided explicitly for a variable or if a variable is missing, model will replace the null value or the missing variable (no variable name in the eventVariables map) with calculated default mean/medians for numeric variables and with special values for categorical variables.
For imported SageMaker models:
If a null value is provided explicitly for a variable, the model and rules will use “null” as the value. If a variable is not provided (no variable name in the eventVariables map), model and rules will use the default value that is provided for the variable.
public GetEventPredictionRequest addEventVariablesEntry(String key, String value)
public GetEventPredictionRequest clearEventVariablesEntries()
public Map<String,ModelEndpointDataBlob> getExternalModelEndpointDataBlobs()
The Amazon SageMaker model endpoint input data blobs.
public void setExternalModelEndpointDataBlobs(Map<String,ModelEndpointDataBlob> externalModelEndpointDataBlobs)
The Amazon SageMaker model endpoint input data blobs.
externalModelEndpointDataBlobs - The Amazon SageMaker model endpoint input data blobs.public GetEventPredictionRequest withExternalModelEndpointDataBlobs(Map<String,ModelEndpointDataBlob> externalModelEndpointDataBlobs)
The Amazon SageMaker model endpoint input data blobs.
externalModelEndpointDataBlobs - The Amazon SageMaker model endpoint input data blobs.public GetEventPredictionRequest addExternalModelEndpointDataBlobsEntry(String key, ModelEndpointDataBlob value)
public GetEventPredictionRequest clearExternalModelEndpointDataBlobsEntries()
public String toString()
toString in class ObjectObject.toString()public GetEventPredictionRequest clone()
AmazonWebServiceRequestclone in class AmazonWebServiceRequestObject.clone()