LabelRulesetGeneration¶

Label ruleset generation step that validates and optimizes user-defined classification rules for transparent, maintainable rule-based label mapping in ML training pipelines


SageMaker step type	`Processing`
Node type	internal (consumes upstream, produces downstream)
Container entry point	`label_ruleset_generation.py`
Interface file	`steps/interfaces/label_ruleset_generation.step.yaml`

Compute¶


Compute kind	`sklearn`

Functionality¶

Label ruleset generation script. Validates and optimizes user-defined classification rules for transparent, maintainable rule-based classification.

Inputs (dependencies)¶

Input	Type	Required	Compatible producers
`ruleset_configs`	`processing_output`	no	RulesetConfiguration, ProcessingStep

Outputs¶

Output	Type
`validated_ruleset`	`processing_output`
`validation_report`	`processing_output`

Consumers (downstream steps)¶

Steps that declare this step as a compatible input source:

LabelRulesetExecution

Framework requirements¶

Package	Version
`pydantic`	`>=2.0.0`
`pandas`	`>=1.3.0`

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