Interface AutoMLAlgorithmConfig.Builder
- All Superinterfaces:
 Buildable,CopyableBuilder<AutoMLAlgorithmConfig.Builder,,AutoMLAlgorithmConfig> SdkBuilder<AutoMLAlgorithmConfig.Builder,,AutoMLAlgorithmConfig> SdkPojo
- Enclosing class:
 AutoMLAlgorithmConfig
- 
Method Summary
Modifier and TypeMethodDescriptionautoMLAlgorithms(Collection<AutoMLAlgorithm> autoMLAlgorithms) The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.autoMLAlgorithms(AutoMLAlgorithm... autoMLAlgorithms) The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.autoMLAlgorithmsWithStrings(String... autoMLAlgorithms) The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.autoMLAlgorithmsWithStrings(Collection<String> autoMLAlgorithms) The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copyMethods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, buildMethods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields 
- 
Method Details
- 
autoMLAlgorithmsWithStrings
The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
 
In
ENSEMBLINGmode:- 
 
"catboost"
 - 
 
"extra-trees"
 - 
 
"fastai"
 - 
 
"lightgbm"
 - 
 
"linear-learner"
 - 
 
"nn-torch"
 - 
 
"randomforest"
 - 
 
"xgboost"
 
 - 
 
 - 
 
In
HYPERPARAMETER_TUNINGmode:- 
 
"linear-learner"
 - 
 
"mlp"
 - 
 
"xgboost"
 
 - 
 
 
- Parameters:
 autoMLAlgorithms- The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
        
In
ENSEMBLINGmode:- 
        
"catboost"
 - 
        
"extra-trees"
 - 
        
"fastai"
 - 
        
"lightgbm"
 - 
        
"linear-learner"
 - 
        
"nn-torch"
 - 
        
"randomforest"
 - 
        
"xgboost"
 
 - 
        
 - 
        
In
HYPERPARAMETER_TUNINGmode:- 
        
"linear-learner"
 - 
        
"mlp"
 - 
        
"xgboost"
 
 - 
        
 
- 
        
 - Returns:
 - Returns a reference to this object so that method calls can be chained together.
 
 - 
 
 - 
autoMLAlgorithmsWithStrings
The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
 
In
ENSEMBLINGmode:- 
 
"catboost"
 - 
 
"extra-trees"
 - 
 
"fastai"
 - 
 
"lightgbm"
 - 
 
"linear-learner"
 - 
 
"nn-torch"
 - 
 
"randomforest"
 - 
 
"xgboost"
 
 - 
 
 - 
 
In
HYPERPARAMETER_TUNINGmode:- 
 
"linear-learner"
 - 
 
"mlp"
 - 
 
"xgboost"
 
 - 
 
 
- Parameters:
 autoMLAlgorithms- The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
        
In
ENSEMBLINGmode:- 
        
"catboost"
 - 
        
"extra-trees"
 - 
        
"fastai"
 - 
        
"lightgbm"
 - 
        
"linear-learner"
 - 
        
"nn-torch"
 - 
        
"randomforest"
 - 
        
"xgboost"
 
 - 
        
 - 
        
In
HYPERPARAMETER_TUNINGmode:- 
        
"linear-learner"
 - 
        
"mlp"
 - 
        
"xgboost"
 
 - 
        
 
- 
        
 - Returns:
 - Returns a reference to this object so that method calls can be chained together.
 
 - 
 
 - 
autoMLAlgorithms
The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
 
In
ENSEMBLINGmode:- 
 
"catboost"
 - 
 
"extra-trees"
 - 
 
"fastai"
 - 
 
"lightgbm"
 - 
 
"linear-learner"
 - 
 
"nn-torch"
 - 
 
"randomforest"
 - 
 
"xgboost"
 
 - 
 
 - 
 
In
HYPERPARAMETER_TUNINGmode:- 
 
"linear-learner"
 - 
 
"mlp"
 - 
 
"xgboost"
 
 - 
 
 
- Parameters:
 autoMLAlgorithms- The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
        
In
ENSEMBLINGmode:- 
        
"catboost"
 - 
        
"extra-trees"
 - 
        
"fastai"
 - 
        
"lightgbm"
 - 
        
"linear-learner"
 - 
        
"nn-torch"
 - 
        
"randomforest"
 - 
        
"xgboost"
 
 - 
        
 - 
        
In
HYPERPARAMETER_TUNINGmode:- 
        
"linear-learner"
 - 
        
"mlp"
 - 
        
"xgboost"
 
 - 
        
 
- 
        
 - Returns:
 - Returns a reference to this object so that method calls can be chained together.
 
 - 
 
 - 
autoMLAlgorithms
The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
 
In
ENSEMBLINGmode:- 
 
"catboost"
 - 
 
"extra-trees"
 - 
 
"fastai"
 - 
 
"lightgbm"
 - 
 
"linear-learner"
 - 
 
"nn-torch"
 - 
 
"randomforest"
 - 
 
"xgboost"
 
 - 
 
 - 
 
In
HYPERPARAMETER_TUNINGmode:- 
 
"linear-learner"
 - 
 
"mlp"
 - 
 
"xgboost"
 
 - 
 
 
- Parameters:
 autoMLAlgorithms- The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLINGorHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.- 
        
In
ENSEMBLINGmode:- 
        
"catboost"
 - 
        
"extra-trees"
 - 
        
"fastai"
 - 
        
"lightgbm"
 - 
        
"linear-learner"
 - 
        
"nn-torch"
 - 
        
"randomforest"
 - 
        
"xgboost"
 
 - 
        
 - 
        
In
HYPERPARAMETER_TUNINGmode:- 
        
"linear-learner"
 - 
        
"mlp"
 - 
        
"xgboost"
 
 - 
        
 
- 
        
 - Returns:
 - Returns a reference to this object so that method calls can be chained together.
 
 - 
 
 
 -