Class AutoMLCandidateGenerationConfig
- All Implemented Interfaces:
Serializable
,SdkPojo
,ToCopyableBuilder<AutoMLCandidateGenerationConfig.Builder,
AutoMLCandidateGenerationConfig>
Stores the configuration information for how a candidate is generated (optional).
- See Also:
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Nested Class Summary
Nested Classes -
Method Summary
Modifier and TypeMethodDescriptionfinal List
<AutoMLAlgorithmConfig> Stores the configuration information for the selection of algorithms trained on tabular data.builder()
final boolean
final boolean
equalsBySdkFields
(Object obj) Indicates whether some other object is "equal to" this one by SDK fields.final String
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job.final <T> Optional
<T> getValueForField
(String fieldName, Class<T> clazz) final boolean
For responses, this returns true if the service returned a value for the AlgorithmsConfig property.final int
hashCode()
static Class
<? extends AutoMLCandidateGenerationConfig.Builder> Take this object and create a builder that contains all of the current property values of this object.final String
toString()
Returns a string representation of this object.Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
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Method Details
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featureSpecificationS3Uri
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input
FeatureAttributeNames
(optional) in JSON format as shown below:{ "FeatureAttributeNames":["col1", "col2", ...] }
.You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types:
numeric
,categorical
,text
, anddatetime
. In HPO mode, Autopilot can supportnumeric
,categorical
,text
,datetime
, andsequence
.If only
FeatureDataTypes
is provided, the column keys (col1
,col2
,..) should be a subset of the column names in the input data.If both
FeatureDataTypes
andFeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided inFeatureAttributeNames
.The key name
FeatureAttributeNames
is fixed. The values listed in["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.- Returns:
- A URL to the Amazon S3 data source containing selected features from the input data source to run an
Autopilot job. You can input
FeatureAttributeNames
(optional) in JSON format as shown below:{ "FeatureAttributeNames":["col1", "col2", ...] }
.You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types:
numeric
,categorical
,text
, anddatetime
. In HPO mode, Autopilot can supportnumeric
,categorical
,text
,datetime
, andsequence
.If only
FeatureDataTypes
is provided, the column keys (col1
,col2
,..) should be a subset of the column names in the input data.If both
FeatureDataTypes
andFeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided inFeatureAttributeNames
.The key name
FeatureAttributeNames
is fixed. The values listed in["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
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hasAlgorithmsConfig
public final boolean hasAlgorithmsConfig()For responses, this returns true if the service returned a value for the AlgorithmsConfig property. This DOES NOT check that the value is non-empty (for which, you should check theisEmpty()
method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified. -
algorithmsConfig
Stores the configuration information for the selection of algorithms trained on tabular data.
The list of available algorithms to choose from depends on the training mode set in
TabularJobConfig.Mode
.-
AlgorithmsConfig
should not be set if the training mode is set onAUTO
. -
When
AlgorithmsConfig
is provided, oneAutoMLAlgorithms
attribute must be set and one only.If the list of algorithms provided as values for
AutoMLAlgorithms
is empty,CandidateGenerationConfig
uses the full set of algorithms for the given training mode. -
When
AlgorithmsConfig
is not provided,CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the
hasAlgorithmsConfig()
method.- Returns:
- Stores the configuration information for the selection of algorithms trained on tabular data.
The list of available algorithms to choose from depends on the training mode set in
TabularJobConfig.Mode
.-
AlgorithmsConfig
should not be set if the training mode is set onAUTO
. -
When
AlgorithmsConfig
is provided, oneAutoMLAlgorithms
attribute must be set and one only.If the list of algorithms provided as values for
AutoMLAlgorithms
is empty,CandidateGenerationConfig
uses the full set of algorithms for the given training mode. -
When
AlgorithmsConfig
is not provided,CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
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toBuilder
Description copied from interface:ToCopyableBuilder
Take this object and create a builder that contains all of the current property values of this object.- Specified by:
toBuilder
in interfaceToCopyableBuilder<AutoMLCandidateGenerationConfig.Builder,
AutoMLCandidateGenerationConfig> - Returns:
- a builder for type T
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builder
-
serializableBuilderClass
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hashCode
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equals
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equalsBySdkFields
Description copied from interface:SdkPojo
Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in anSdkPojo
class, and is generated based on a service model.If an
SdkPojo
class does not have any inherited fields,equalsBySdkFields
andequals
are essentially the same.- Specified by:
equalsBySdkFields
in interfaceSdkPojo
- Parameters:
obj
- the object to be compared with- Returns:
- true if the other object equals to this object by sdk fields, false otherwise.
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toString
-
getValueForField
-
sdkFields
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sdkFieldNameToField
- Specified by:
sdkFieldNameToField
in interfaceSdkPojo
- Returns:
- The mapping between the field name and its corresponding field.
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