Class: Aws::SageMaker::Types::AutoMLChannel
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::AutoMLChannel
- Defined in:
- gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb
Overview
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#channel_type ⇒ String
The channel type (optional) is an
enum
string. -
#compression_type ⇒ String
You can use
Gzip
orNone
. -
#content_type ⇒ String
The content type of the data from the input source.
-
#data_source ⇒ Types::AutoMLDataSource
The data source for an AutoML channel.
-
#sample_weight_attribute_name ⇒ String
If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model.
-
#target_attribute_name ⇒ String
The name of the target variable in supervised learning, usually represented by 'y'.
Instance Attribute Details
#channel_type ⇒ String
The channel type (optional) is an enum
string. The default value
is training
. Channels for training and validation must share the
same ContentType
and TargetAttributeName
. For information on
specifying training and validation channel types, see How to
specify training and validation datasets.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |
#compression_type ⇒ String
You can use Gzip
or None
. The default value is None
.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |
#content_type ⇒ String
The content type of the data from the input source. You can use
text/csv;header=present
or x-application/vnd.amazon+parquet
. The
default value is text/csv;header=present
.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |
#data_source ⇒ Types::AutoMLDataSource
The data source for an AutoML channel.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |
#sample_weight_attribute_name ⇒ String
If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |
#target_attribute_name ⇒ String
The name of the target variable in supervised learning, usually represented by 'y'.
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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 2089 class AutoMLChannel < Struct.new( :data_source, :compression_type, :target_attribute_name, :content_type, :channel_type, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end |