TemporalFeatureEngineering

Temporal feature engineering step that extracts comprehensive temporal features from normalized sequences for machine learning models

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

Compute

Compute kind	sklearn

Functionality

Temporal feature engineering script. Extracts comprehensive temporal features from normalized sequence data combining generic temporal features with time window aggregations.

Inputs (dependencies)

Input	Type	Required	Compatible producers
normalized_sequences	processing_output	yes	TemporalSequenceNormalization, ProcessingStep

Outputs

Output	Type
temporal_feature_tensors	processing_output

Consumers (downstream steps)

Steps that declare this step as a compatible input source:

• BedrockBatchProcessing

• BedrockProcessing

• LabelRulesetExecution

• PseudoLabelMerge

• TSATraining

Framework requirements

Package	Version
pandas	>=1.3.0
numpy	>=1.21.0

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