Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation

Returns a new instance of GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation.



22013
22014
22015
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22013

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#auto ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation

Training pipeline will infer the proper transformation based on the statistic of dataset. Corresponds to the JSON property auto

Returns:



21944
21945
21946
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21944

def auto
  @auto
end

#categorical ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation

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

Returns:



21954
21955
21956
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21954

def categorical
  @categorical
end

#numeric ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation

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

Returns:



21965
21966
21967
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21965

def numeric
  @numeric
end

#repeated_categorical ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation

Treats the column as categorical array and performs following transformation functions. * For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Empty arrays treated as an embedding of zeroes. Corresponds to the JSON property repeatedCategorical

Returns:



21974
21975
21976
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21974

def repeated_categorical
  @repeated_categorical
end

#repeated_numeric ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation

Treats the column as numerical array and performs following transformation functions. * All transformations for Numerical types applied to the average of the all elements. * The average of empty arrays is treated as zero. Corresponds to the JSON property repeatedNumeric

Returns:



21981
21982
21983
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21981

def repeated_numeric
  @repeated_numeric
end

#repeated_text ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation

Treats the column as text array and performs following transformation functions. * Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns. * Empty arrays treated as an empty text. Corresponds to the JSON property repeatedText

Returns:



21990
21991
21992
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 21990

def repeated_text
  @repeated_text
end

#text ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation

Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Tokenization is based on unicode script boundaries.

  • Missing values get their own lookup index and resulting embedding. * Stop- words receive no special treatment and are not removed. Corresponds to the JSON property text

Returns:



22001
22002
22003
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22001

def text
  @text
end

#timestamp ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation

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

Returns:



22011
22012
22013
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22011

def timestamp
  @timestamp
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



22018
22019
22020
22021
22022
22023
22024
22025
22026
22027
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 22018

def update!(**args)
  @auto = args[:auto] if args.key?(:auto)
  @categorical = args[:categorical] if args.key?(:categorical)
  @numeric = args[:numeric] if args.key?(:numeric)
  @repeated_categorical = args[:repeated_categorical] if args.key?(:repeated_categorical)
  @repeated_numeric = args[:repeated_numeric] if args.key?(:repeated_numeric)
  @repeated_text = args[:repeated_text] if args.key?(:repeated_text)
  @text = args[:text] if args.key?(:text)
  @timestamp = args[:timestamp] if args.key?(:timestamp)
end