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
copy
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods 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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"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 (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"linear-learner"
-
"mlp"
-
"xgboost"
-
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
-