Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation
- Includes:
- Core::Hashable, Core::JsonObjectSupport
- Defined in:
- lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb
Instance Attribute Summary collapse
-
#auto ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation
Training pipeline will infer the proper transformation based on the statistic of dataset.
-
#categorical ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation
Training pipeline will perform following transformation functions.
-
#numeric ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation
Training pipeline will perform following transformation functions.
-
#text ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation
Training pipeline will perform following transformation functions.
-
#timestamp ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation
Training pipeline will perform following transformation functions.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation
constructor
A new instance of GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation
Returns a new instance of GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation.
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26294 def initialize(**args) update!(**args) end |
Instance Attribute Details
#auto ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation
Training pipeline will infer the proper transformation based on the statistic
of dataset.
Corresponds to the JSON property auto
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26253 def auto @auto end |
#categorical ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation
Training pipeline will perform following transformation functions. * The
categorical string as is--no change to case, punctuation, spelling, tense, and
so on. * Convert the category name to a dictionary lookup index and generate
an embedding for each index. * Categories that appear less than 5 times in the
training dataset are treated as the "unknown" category. The "unknown" category
gets its own special lookup index and resulting embedding.
Corresponds to the JSON property categorical
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26263 def categorical @categorical end |
#numeric ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation
Training pipeline will perform following transformation functions. * The value
converted to float32. * The z_score of the value. * log(value+1) when the
value is greater than or equal to 0. Otherwise, this transformation is not
applied and the value is considered a missing value. * z_score of log(value+1)
when the value is greater than or equal to 0. Otherwise, this transformation
is not applied and the value is considered a missing value. * A boolean value
that indicates whether the value is valid.
Corresponds to the JSON property numeric
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26274 def numeric @numeric end |
#text ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation
Training pipeline will perform following transformation functions. * The text
as is--no change to case, punctuation, spelling, tense, and so on. * Convert
the category name to a dictionary lookup index and generate an embedding for
each index.
Corresponds to the JSON property text
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26282 def text @text end |
#timestamp ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation
Training pipeline will perform following transformation functions. * Apply the
transformation functions for Numerical columns. * Determine the year, month,
day,and weekday. Treat each value from the timestamp as a Categorical column. *
Invalid numerical values (for example, values that fall outside of a typical
timestamp range, or are extreme values) receive no special treatment and are
not removed.
Corresponds to the JSON property timestamp
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26292 def @timestamp end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 26299 def update!(**args) @auto = args[:auto] if args.key?(:auto) @categorical = args[:categorical] if args.key?(:categorical) @numeric = args[:numeric] if args.key?(:numeric) @text = args[:text] if args.key?(:text) @timestamp = args[:timestamp] if args.key?(:timestamp) end |